text:
Hands-on TensorBoard example issue on TF 1.0.0 Win GPU

Environment info
Operating System: Windows 10.0.14393, latest patches
Installed version of CUDA and cuDNN:
nvcc --version says 8.0.44; CUDA is 8.0, cuDNN is 5.1
05.09.2016  15:51            87.834 cuda.lib
05.09.2016  15:51           681.064 cudadevrt.lib
05.09.2016  15:51            64.550 cudart.lib
05.09.2016  15:51         2.318.456 cudart_static.lib
27.07.2016  09:35            37.452 cudnn.lib
Anaconda 4.2.0
pip install --ignore-installed --upgrade tensorflow
tensorflow.version 1.0.0
I ran the
example from Dandelion Mane's Hands-on TensorBoard talk at TF Dev Summit 2017
What other attempted solutions have you tried?
It works with TF 1.0.0 on Ubuntu 16.04, both CPU and GPU versions.
Logs or other output that would be helpful
On TF Windows GPU (versions as noted above):
(tensorflow) C:\dl\tf\mnist_tutorial>python mnist_tutorial.py

Successfully downloaded train-images-idx3-ubyte.gz 9912422 bytes.
Extracting log/data\train-images-idx3-ubyte.gz
...
Extracting log/data\t10k-labels-idx1-ubyte.gz
Starting run for lr_1E-04,conv=2,fc=2
E c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel ('op: "BestSplits" device_type: "CPU"') for unknown op: BestSplits
E c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel ('op: "CountExtremelyRandomStats" device_type: "CPU"') for unknown op: CountExtremelyRandomStats
...

Thanks
G.

This should be working... is there any problem apart from the logged errors about unknown ops (which are fixed at HEAD, but you can safely ignore)?

Closing due to lack of activity.  Please reopen if necessary.

authors: ai-bits mrry prb12


text:
How Do I Reach Out Gemini Support Number

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➡For help with ❞Gemini Support Number❞, reach out to our support team anytime at 📲 1-510-989-6343   We're available 24*7 to assist with installation.
➡ For Gemini Support, please feel free to contact our support team at 📲 1-510-989-6343   We can assist with installation, setup, and troubleshooting

Closing this issue as spam.

source: gharchive/issue

repo: tensorflow/tensorflow

license_type: permissive

license_source: github-api


text:
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.ccvcv

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### 𝖶𝖺𝗍𝖼𝗁 🟢 ➤ ➤ ➤ 🌐 𝖢𝗅𝗂𝖼𝗄 𝖧𝖾𝗋𝖾 𝖳𝗈 𝗅𝗂𝗇𝗄 (𝖥𝗎𝗅 𝗅 𝖵𝗂𝗋𝖺𝗅 𝖵𝗂𝖽𝖾𝗈 𝖫𝗂𝗇𝗄)
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### 𝖶𝖺𝗍𝖼𝗁 🟢 ➤ ➤ ➤ 🌐 𝖢𝗅𝗂𝖼𝗄 𝖧𝖾𝗋𝖾 𝖳𝗈 𝗅𝗂𝗇𝗄 (𝖥𝗎𝗅 𝗅 𝖵𝗂𝗋𝖺𝗅 𝖵𝗂𝖽𝖾𝗈 𝖫𝗂𝗇𝗄)
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### 𝖶𝖺𝗍𝖼𝗁 🟢 ➤ ➤ ➤ 🌐 𝖢𝗅𝗂𝖼𝗄 𝖧𝖾𝗋𝖾 𝖳𝗈 𝗅𝗂𝗇𝗄 (𝖥𝗎𝗅 𝗅 𝖵𝗂𝗋𝖺𝗅 𝖵𝗂𝖽𝖾𝗈 𝖫𝗂𝗇𝗄)
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### 𝖶𝖺𝗍𝖼𝗁 🟢 ➤ ➤ ➤ 🌐 𝖢𝗅𝗂𝖼𝗄 𝖧𝖾𝗋𝖾 𝖳𝗈 𝗅𝗂𝗇𝗄 (𝖥𝗎𝗅 𝗅 𝖵𝗂𝗋𝖺𝗅 𝖵𝗂𝖽𝖾𝗈 𝖫𝗂𝗇𝗄)
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### 🔴 ➤► 𝖣𝖮𝖶𝖭𝖫𝖮𝖠𝖣👉👉 (𝖥𝗎𝗅𝗅 𝖵𝗂𝗋𝖺𝗅 𝖵𝗂𝖽𝖾𝗈 𝖫𝗂𝗇 𝗄)
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### 𝖶𝖺𝗍𝖼𝗁 🟢 ➤ ➤ ➤ 🌐 𝖢𝗅𝗂𝖼𝗄 𝖧𝖾𝗋𝖾 𝖳𝗈 𝗅𝗂𝗇𝗄 (𝖥𝗎𝗅 𝗅 𝖵𝗂𝗋𝖺𝗅 𝖵𝗂𝖽𝖾𝗈 𝖫𝗂𝗇𝗄)
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### 🔴 ➤► 𝖣𝖮𝖶𝖭𝖫𝖮𝖠𝖣👉👉 (𝖥𝗎𝗅𝗅 𝖵𝗂𝗋𝖺𝗅 𝖵𝗂𝖽𝖾𝗈 𝖫𝗂𝗇 𝗄)
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authors: bklidardk ghost redfref


text:
separable_conv2d() got an unexpected keyword argument 'rate'

When running :
model = Xception(include_top=True, weights='imagenet')

I'm getting this error :
Traceback (most recent call last):
  File "/home/username/PycharmProjects/segmentation/data/xception.py", line 273, in <module>
    model = Xception(include_top=True, weights='imagenet')
  File "/home/username/PycharmProjects/segmentation/data/xception.py", line 155, in Xception
    x = SeparableConv2D(128, (3, 3), padding='same', use_bias=False, name='block2_sepconv1')(x)
  File "/home/username/.virtualenvs/cv/lib/python3.5/site-packages/keras/engine/topology.py", line 578, in __call__
    output = self.call(inputs, **kwargs)
  File "/home/username/.virtualenvs/cv/lib/python3.5/site-packages/keras/layers/convolutional.py", line 986, in call
    padding=self.padding)
  File "/home/username/.virtualenvs/cv/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py", line 2967, in separable_conv2d
    rate=dilation_rate)
TypeError: separable_conv2d() got an unexpected keyword argument 'rate'

It looks like you are using an outdated version of TensorFlow where tf.nn.separable_conv2d did not yet support the rate argument. Update to the latest version.

authors: Raniazy fchollet


text:
convert a tensor to matrix

Hi,
output of first layer cnn , "if  input was a image with size[100,150] then the output layer is a tensor (1,100,150,32)"
for slicing The first image from all 32 output images, i used this code:
conv1 = tf.layers.conv2d( image, filters=32, kernel_size=[5, 5], padding="same", activation=tf.nn.relu)
first_image=slice(conv1,[0,0,0,0],[1, 100, 152, 1])

conv1 is  tensor (1, 100, 150 ,32)
first_image is tensor (1, 100 ,150 , 1)

has the Tensorflow  a command for convert a tensor to 2-D matrix directly ?, or how can convert a tensor to matrix in Tensorflow?

You can reshape a tensor using tf.reshape, if that's what you need.
There might be a function here: https://www.tensorflow.org/api_guides/python/array_ops#Shapes_and_Shaping that might help you.
This question is better asked on  StackOverflow since it is not a  bug or feature request. There is also a larger community that reads questions there. Thanks!

authors: drpngx jeansely


text:
grad of variable size extract_image_patches

Fixes #11651
cc: @drpngx @gpapan

@gpapan could you take a look?

Nagging Reviewer @sherrym: It has been 14 days with no activity and the awaiting review label was assigned. Can you please take a look?

What time it will be with an official version about "grad of variable size extract_image_patches"

Nagging Reviewer @sherrym: It has been 15 days with no activity and the awaiting review label was assigned. Can you please take a look?

Nagging Reviewer @sherrym: It has been 30 days with no activity and the awaiting review label was assigned. Can you please take a look?

Nagging Reviewer @sherrym: It has been 45 days with no activity and the awaiting review label was assigned. Can you please take a look?

Nagging Reviewer @sherrym: It has been 60 days with no activity and the awaiting review label was assigned. Can you please take a look?

Nagging Reviewer @sherrym: You have been added as a reviewer to this pull request. Please add your review or reassign. It has been 75 days with no activity and the awaiting review label has been applied.

Nagging Reviewer @sherrym: You have been added as a reviewer to this pull request. Please add your review or reassign. It has been 89 days with no activity and the awaiting review label has been applied.

Nagging Reviewer @sherrym: You have been added as a reviewer to this pull request. Please add your review or reassign. It has been 105 days with no activity and the awaiting review label has been applied.

Nagging Reviewer @sherrym: You have been added as a reviewer to this pull request. Please add your review or reassign. It has been 120 days with no activity and the awaiting review label has been applied.

@robieta can you take a look?

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Apologies; this got lost in my inbox. Can you check whether this is still an issue, and if so rebase your PR?

Any news of this PR?

New PR has been opened with these changes , so closing this .Thank you

source: gharchive/pull-request

authors: HiZhongfei drpngx fmannan lioutasb martinwicke robieta rthadur tensorflowbutler


text:
[Features] Support more types for Partitionedvariable assginment method

This pull request enhances PartitionedVariable assignment function.  List and PartitionedVariable types is supported for right value. Any comments are welcome.

Hi  @alextp,
This is the enhancement of https://github.com/tensorflow/tensorflow/pull/22473 . Please review it.
Thanks.


text:
Porting the Pooling kernel to Tensorflow Lite Micro with MaxPool support

This PR ports the MaxPool-part of the pooling kernel from Tensorflow Lite to Tensorflow Lite Micro.

Hi Jens,
I've added pooling.cc for avg_pool. Please merge.
Thanks.

The force-push is due to rebasing PR onto master, and no code have been added.

@jenselo can you please check build failures. Thanks !

@jenselo can you please check build failures. Thanks !

Yes, I'll take a look.

It seems that the test case that fails is the testStableName in the //tensorflow/python:function_test tests (or function_test_gpu in the Linux GPU build).
For the Linux GPU build the batch_matmul_test in //tensorflow/python/compiler/tensorrt.
I've also ran the function_test locally with the maxpool patches and didn't see the error.
Do changes made in tensorflow/lite/experimental/micro have any impact to the tests in tensorflow/python?

authors: gbaned jenselo wangtz


text:
Use zeros_like(x) in favour of zeros(shape(x)) when computing gradients

This PR uses zeros_like(x) in favour of zeros(shape(x)) in gradient definitions.
This simplifies the code and slightly improves performance since it can use the fused ZerosLike kernel instead of requiring both Shape and Zeros.

Thanks for the cleanup! We appreciate it!

My changes in eager/function.py broke the while_v2 unittests for some reason. I reverted the changes causing this failure.

authors: kkimdev lgeiger


text:
"ZeroDivisionError: integer division or modulo by zero" while backpropagating #51653

"ZeroDivisionError: integer division or modulo by zero" while backpropagating #51653
logic reference:
https://github.com/tensorflow/tensorflow/issues/51653#issuecomment-904756234

@sannamir  Can you please sign CLA. Thanks!

@googlebot I signed it!

@sannamir  Can you please check @allenlavoie's comments and resolve conflicts?. Thanks!

@sannamir Any update on this PR? Please. Thanks!

It has passed all checks.

It has a conflict

@sannamir  Can you please resolve conflicts? Thanks!

@sannamir Any update on this PR? Please. Thanks!

I'm going to go ahead and close this PR, because it seems to have stalled. If you're still interested in pursing this (and responding to my comments), please feel free to reopen!

authors: gbaned mihaimaruseac sannamir


text:
[TF-TRT] Adding Graph Visualization Export Instrumentation

This PR introduces a  TF-TRT graph visualization export tool in graphviz format.
The user can then convert the graphviz file in .dot format to a more commonly readable format like PNG.
Example NNUnet 2D TF2:

Usage: TF_TRT_EXPORT_GRAPH_VIZ_PATH=/path/to/mymodel.dot python main.py

@bixia1 for review
CC: @tfeher @christopherbate

@DEKHTIARJonathan It is nice to show an example of the graph here. But would you please move the graph example out of the PR description and put it in a comment block?

Example with Electra TF2:

@DEKHTIARJonathan Can you please resolve conflicts? Thanks!

@bixia1 I have finished reworking this PR. It now includes the following:

compute device per node
coloring per compute dtype

@bixia1 I have finished reworking this PR. It now includes the following:

compute device per node
coloring per compute dtype

Please review

@bixia1 comments addressed. Please review

@bixia1 any problem with this PR ? It's approved and not merged for 2 days

authors: DEKHTIARJonathan bixia1 gbaned


text:
Update tensorflow2 code

In this version, we use tf.compat.v1.enable_v2_behavior() and tf.compat.v1.disable_v2_behavior() instead of directly using _pywrap_tf2. Additionally, the function is_tf2_behavior_enabled() now uses tf.executing_eagerly() instead of _pywrap_tf2.is_enabled(), which is the recommended way to check if TensorFlow 2.0 behavior is enabled.

Hi @pkanwar23 Can you please review this PR ? Thank you!

authors: gbaned yasirulhadi


text:
Assert Bazel version from tf_workspace()

This ensures that projects depending on TensorFlow, e.g. TFServing, will
benefit from the version check.
The mandatory version has also been bumped up to Bazel 0.4.4 which has been out
for 21 days. It includes numerous very important fixes. TensorFlow also appears
to not work without it.
CC: @martinwicke

Leaving the test failures aside, the details of the change look reasonable.  However, @martinwicke's a better person to answer whether we want to force people to upgrade.  It may be that Bazel 0.4.4 is only required by folks using TensorFlow as a submodule or via http_archive.
One cludgy option if forcing everyone to upgrade is bad: we could require 0.4.4 for anyone calling tf_workspace except for tensorflow/WORKSPACE itself, via an extra boolean flag to tf_workspace.

We've traditionally been tracking bazel close to head, so I have no problem requiring fresh bazel versions. Historically, the threshold has been "Is it in homebrew yet?", which has usually happened a few days after release.
So I like this change, but it does mean that we need to upgrade our test machines to have the new bazel (i.e. change the bazel version in ci_build/install/install_bazel.sh, and then wait while we update all the other machines that don't use docker before we merge this.

0.4.4 is in Homebrew.  I just updated to it on my laptop with brew update bazel.

0.4.4 breaks TF build, so we cannot use it. (There is a post mortem for the release).
We have to wait for 0.4.5 to bump our bazel dependency.

What happened?
On Thu, Feb 23, 2017 at 1:07 AM, gunan notifications@github.com wrote:

0.4.4 breaks TF build, so we cannot use it. (There is a post mortem for
the release).
We have to wait for 0.4.5 to bump our bazel dependency.
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/tensorflow/tensorflow/pull/7799#issuecomment-281935397,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AADAbhgY-kjhFPp9zJI0qPml1afx1zhWks5rfUxggaJpZM4MJSz-
.

If Bazel 0.4.4 is broken, this is problematic for deepmath including tensorflow as a submodule.  Using it as a submodule does not work with 0.4.3.  Is there a workaround that will make 0.4.4 work?  Otherwise I'll end up blocked for a long time.

0.4.5 RC came out yesterday, so it may not be a long time.

Jenkins, test this please.

Jenkins, test this please.

Updated and testing.

authors: girving gunan jart maciekcc martinwicke


text:
Move spawn_strategy args from install docs to bazelrc.

--spawn_strategy=standalone is pretty much always required to avoid problems with hermetic builds excluding system files, so we make it the default in the bazelrc file. This simplifies the installation instructions.

merged.


text:
WIP Switch To mkdocs

Motivation and Context
Why is this change required? What problem does it solve?:
better documentation generator.
Does not work at the current moment (unhappy with API plugin for numpy style docstrings).
Types of changes
What types of changes does your code introduce? Put an x in all the boxes that apply:

[x] Documentation update
[ ] Bug fix (non-breaking change which fixes an issue)
[ ] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to change)

Is this PR ready for review, or a work in progress?

[ ] Ready for review
[x] Work in progress

How Has This Been Tested?
Put an x in the boxes that apply:

[ ] Current tests cover modifications made
[ ] New tests have been added to the test suite
[ ] Modifications were made to existing tests to support these changes
[ ] Tests may be needed, but they are not included when the PR was proposed
[ ] I don't know. Help!

Checklist:

[ ] My code follows the code style of this project.
[ ] My change requires a change to the documentation.
[ ] I have updated the documentation accordingly.
[ ] I have read the CONTRIBUTING document.
[ ] I have signed (or will sign when prompted) the tensorwork CLA.
[ ] I have added tests to cover my changes.
[ ] All new and existing tests passed.

The RTD build is failing because this PR deletes docs/requirements.txt 😅

Now RTD is able to compile the docs but there are no docs here https://hangar-py--213.org.readthedocs.build/en/213/
BTW I just found this paragraph on the mkdocs documentation (https://mkdocs.readthedocs.io/en/stable/user-guide/deploying-your-docs/#read-the-docs):

To benefit from all of the features offered by Read the Docs, you will need to use the Read the Docs theme which ships with MkDocs. The various themes which may be referenced in Read the Docs' documentation are Sphinx specific themes and will not work with MkDocs.

What do we do know?

authors: alessiamarcolini rlizzo

repo: tensorwerk/hangar-py


text:
Proposal: Implement anyhow for our errors

Currently, we implement errors as an Enum in error.rs and this crate::error::Error implements level(&self) -> tracing::Level, status_code(&self)-> StatusCode, log(&self), Display, and IntoResponse. We also define a trait ResultExt that provides a convenience method we use widely ok_or_log(self).
The anyhow crate is the most widely used crate for Rust applications and I suggest we move towards it. I believe this is needed because we need to be able to attach context to errors as they propagate up the call stack. In particular I think it's important to include the function_name, variant_name, model_provider_name, inference_id, and episode_id if applicable to errors so that people can more easily understand what was happening when this error occured.
use anyhow::{Context, Result};

fn main() -> Result<()> {
    ...
    model.infer(args).with_context(|| format!("model_id={model_id}")?;

    ...
}

One con is that this error crate is inconvenient for library code since it makes the type underneath opaque to the caller as all errors become anyhow::Error.  This is OK for us as the gateway is an application and doesn't need to export typed errors, but if we ever want to pull out some of our code as library code that might get reused it is probably good to then rip anyhow from those also.
Another con is that due to the orphan rule in Rust, we can't directly implement all our traits on anyhow::Error. However, the axum folks give an example of the newtype pattern here for implementing IntoResponse. We can use a combination of this pattern and downcasting to keep all existing functionality.
One further con is that our error messages are going to get long with all this additional context. I think this is worthwhile.

Decided not to go this direction in favor of changing the way the logs are handled in #473 so that they already contain the context from the spans they are part of.

repo: tensorzero/tensorzero


text:
feat(ui): Add sidebar with separator and sheet component

[!IMPORTANT]
Add new sidebar, separator, and sheet components to the UI, integrating them into the app layout with updated styles and dependencies.

Components:

Add Separator in separator.tsx for UI separation.
Add Sheet in sheet.tsx for dialog-like UI elements.
Add Sidebar in sidebar.tsx with subcomponents like SidebarProvider, SidebarTrigger, SidebarContent, etc.
Add AppSidebar in app.sidebar.tsx for app-specific sidebar implementation.
Add Tooltip in tooltip.tsx for enhanced UI interactions.

Hooks:

Add useIsMobile in use-mobile.tsx to detect mobile viewports.

Integration:

Update root.tsx to include AppSidebar and SidebarProvider in the main app layout.

Styling:

Update tailwind.css with new CSS variables for sidebar styling.

Dependencies:

Add new dependencies in package.json for Radix UI components and other utilities.

This description was created by  for 82432708090073c22385037a280aad9d33e29bee. It will automatically update as commits are pushed.

Thanks!
I updated the PR to match the v0 design a bit more. The top separator wasn't aligned with the separator in the page titles so I removed it.
@virajmehta need your review now

@ellipsis-dev pls review

I have added a separate layout for dashboard routes, so now the sidebar will only be visible in dashboard routes like fine-tuning, etc. Previously, we had a common layout which caused the sidebar to be visible on the home page as well.

hey @ChetanXpro - let's keep it in the homepage too. later we'll want to display more of a summary view there, so the sidebar will be relevant. we'll merge the previous commit so no changes needed. thanks!

Sounds good!

authors: ChetanXpro GabrielBianconi


text:
Perf-Mon: Fetch core clock from the device api instead of hard coding

At the moment clock is hard coded to 1.2Ghz in the profiler module. This clock needs to be extracted from the device api.

@mo-tenstorrent is still relevant?

No

authors: davorchap mo-tenstorrent

repo: tenstorrent-metal/tt-metal


text:
[minor issue] deadlock when no TT devices present

I tested this example. Since I do not have a TT device on my machine, I expected it fails but a deadlock is unexpected.
It stopped at this line when no TT devices present.
Log from tt-buda:
...
2024-06-02 19:46:05.045 | DEBUG    | pybuda.device:run_next_command:455 - Received COMPILE command on TTDevice 'auto_tt0' / 11430
2024-06-02 19:46:05.045 | DEBUG    | pybuda.ttdevice:compile_for:785 - Compiling for Inference mode on TTDevice 'auto_tt0'
2024-06-02 19:46:05.045 | INFO     | Runtime         - No silicon devices detected.
2024-06-02 19:46:05.046 | INFO     | Runtime         - No silicon devices detected.
2024-06-02 19:46:05.046 | ERROR    | pybuda.device:run_next_command:469 - Compile error: No Tenstorrent devices present.
Traceback (most recent call last):
  File "/home/jaebaek/tt-buda/pybuda/pybuda/device.py", line 458, in run_next_command
    ret = self.compile_for(
  File "/home/jaebaek/tt-buda/pybuda/pybuda/ttdevice.py", line 808, in compile_for
    device_cfg=self.get_device_config(compiler_cfg),
  File "/home/jaebaek/tt-buda/pybuda/pybuda/ttdevice.py", line 199, in get_device_config
    raise RuntimeError("No Tenstorrent devices present.")
RuntimeError: No Tenstorrent devices present.

Traceback (most recent call last):
  File "test.py", line 26, in <module>
    test_module_direct_pytorch()
  File "test.py", line 21, in test_module_direct_pytorch
    output = pybuda.PyTorchModule("direct_pt", PyTorchTestModule()).run(input1, input2)
  File "/home/jaebaek/tt-buda/pybuda/pybuda/module.py", line 95, in run
    output_q = pybuda.run_inference(self, inputs=[args])
  File "/home/jaebaek/tt-buda/pybuda/pybuda/run/api.py", line 90, in run_inference
    return _run_inference(module, inputs, input_count, output_queue, _sequential, _perf_trace, _verify_cfg)
  File "/home/jaebaek/tt-buda/pybuda/pybuda/run/impl.py", line 277, in _run_inference
    return _run_devices_inference(
  File "/home/jaebaek/tt-buda/pybuda/pybuda/run/impl.py", line 467, in _run_devices_inference
    output_queue = _initialize_pipeline(False, output_queue, sequential=sequential, verify_cfg=verify_cfg)
  File "/home/jaebaek/tt-buda/pybuda/pybuda/run/impl.py", line 414, in _initialize_pipeline
    _compile_devices(sequential, training=training, sample_inputs=sample_inputs, sample_targets=sample_targets, microbatch_count=microbatch_count, verify_cfg=verify_cfg)
  File "/home/jaebaek/tt-buda/pybuda/pybuda/run/impl.py", line 1248, in _compile_devices
    raise ret
RuntimeError: No Tenstorrent devices present.
2024-06-02 19:46:05.047 | DEBUG    | pybuda.run.impl:_shutdown:1265 - PyBuda shutdown

@jaebaek can you expand on more details as to what the issue is? From our perspective, TT-Buda threw the correct error as no TT Devices were present.

Hi, this is not a critical issue (it does not really bothers me).
The problem is the line 1276 of impl.py#L1276. IIUC, it is supposed to complete _shutdown(..) function and ends the program execution. However, it actually does not ends the program, but it is just stuck in ctx.final_barrier.wait(). It looks like a deadlock. The program termination does not happen. I have to kill it using Ctrl + C.

I tested tt-buda more. I think for all failures, it does not terminate the execution. It seems to have the same dead lock.

@nvukobratTT I see you have worked on the impl.py file before do you know who could take a look at fixing this ? Maybe this needs to be wrapped in a try/except clause? Let me know your thoughts.

Given our current priorities this will not be fixed. Please follow our progress in https://github.com/tenstorrent/tt-mlir

authors: jaebaek milank94 staylorTT

repo: tenstorrent/tt-buda


text:
[Bug Report] "Unknown board type for chip 0" warning when using latest tt-metal on Grayskull e75.

Describe the bug
With the latest tt-metal build, I find it triggering the warning Unknown board type for chip 0. This might happen because chip is running old firmware. Defaulting to DEFAULT with my e75 card.
To Reproduce
Steps to reproduce the behavior:

Compile and build the latest tt-metal
Run one of the Metal programming examples
Observe the following warning

➜  build git:(main) ✗ pwd
/home/marty/Documents/not-my-projects/tt-metal/build
➜  build git:(main) ✗ programming_examples/loopback
                 Device | INFO     | Opening user mode device driver
  Detecting chips (found 1)
2024-11-21 07:37:49.395 | WARNING  | SiliconDriver   - Unknown board type for chip 0. This might happen because chip is running old firmware. Defaulting to DEFAULT
2024-11-21 07:37:49.404 | INFO     | SiliconDriver   - Detected 1 PCI device : [0]
2024-11-21 07:37:49.404 | WARNING  | SiliconDriver   - Unknown board type for chip 0. This might happen because chip is running old firmware. Defaulting to DEFAULT
                  Metal | INFO     | Initializing device 0. Program cache is NOT enabled
                  Metal | INFO     | AI CLK for device 0 is:   1000 MHz
                  Metal | INFO     | Closing device 0
                  Metal | INFO     | Disabling and clearing program cache on device 0
                   Test | INFO     | Test Passed
                 Device | INFO     | Closing user mode device drivers

Expected behavior
e75 should be correctly recognized
Screenshots
If applicable, add screenshots to help explain your problem.
Please complete the following environment information:

OS: Arch Linux
Commit: 75868aad6a85f5a4dea37d5c849fe3be6a42e2e4
Card: Grayskull e75
FW: 80.13.2.0

Additional context
Add any other context about the problem here.

This issue belongs w/ UMD, Pavle recently added this code.

Oops, sorry clocked the wrong button while going through my list.

@pjanevskiTT Do you have an update on this issue ?

@pjanevskiTT Hello, can you please provide an update on the progress or estimated resolution timeline for this item? TY

Hey, sorry for the delay, had a lot of other work on umd. Fixing this issue tomorrow

Close as solution merged.

authors: marty1885 pgkeller pjanevskiTT prajaramanTT zzigler-tt

repo: tenstorrent/tt-metal


text:
JSON Errors need to be lifted to schema driven JSON-LD

We are currently returning ad-hoc javascript objects. These really need to conform to the ontology to which they refer, together with a context object so they can be statelessly interpreted, with a valid '@type'.  Should there be a seperate API ontology for talking about interchange messages? Should it all live in "vio"? Or is "vio" meant only for data conformance checking.

These are now correctly documented in the API and VIO ontologies

repo: terminusdb/terminusdb-server


text:
Numerical Continuation

Re-implementation of Jacobian-Free Newton-Krylov method based continuation library
https://github.com/termoshtt/continuate

Create another repository https://github.com/termoshtt/continuate.rs

repo: termoshtt/eom

license: MIT


text:
Incorrect "Parenthesized pattern" error in 4.0.5

require('acorn').parse('(foo = [])[0] = 4;')

reproduces. Note that it is ES5-only and contains no patterns.
Originally reported in https://github.com/zloirock/core-js/issues/277

https://github.com/nodeca/nodeca.users/blob/master/lib/identicon.js#L39-L49
4.0.7 still has this error with this code. I know it's ugly, but it works and 4.0.4 was ok. Reopen please.

https://github.com/jbt/js-crypto/blob/master/sha1.js better link to test 4.0.7 in es5 mode for "Parenthesized pattern" bug.

A trimmed down example would appear to be
[
  (G = s),
  F = G,
]

Patch 963475609f569 and release 4.0.8 should hide this problem. Opened #503 to track a real solution.

I confirm, no problems with 4.0.8. Thanks a lot!

authors: loganfsmyth marijnh puzrin

repo: ternjs/acorn

license: mit

license_source: bigquery


text:
Support TLS ALPN policies for the NLB

Is your request related to a new offering from AWS?

Yes, since the middle of 2020.
Is your request related to a problem? Please describe.

No, but would be nice to support it if we want to use HTTP2 for our apps behind a NLB.
Describe the solution you'd like.

Add a variable as it's already done for the https_listener
alpn_policy     = lookup(var.https_listeners[count.index], "alpn_policy", null)
Describe alternatives you've considered.

Additional context

"Elastic Load Balancing now supports TLS ALPN policies for Network Load Balancers. Using TLS offloading with ALPN policies you can now offload your application’s TLS HTTP/2 traffic decryption/encryption logic to the Network Load Balancer, improving your service security posture and reducing operational complexity.  " It would really be nice to have this in terraform.

I literally need this right now 👍🏻  x 1000

/reopen

PR is welcome!

Ok, I'll try to come up with one in the following days, depending on my travels. Thanks Anton and best of luck 🙂

Please reopen this issue until I have time to create a PR.

authors: Erokos antonbabenko er1c

repo: terraform-aws-modules/terraform-aws-alb


text:
feat: Add support for creating IAM role/instance profile with policies

Description

Add support for creating IAM role/instance profile with policies
Add support for providing AMI vis SSM parameter like Amazon AMIs

Motivation and Context

Instance profiles are the preferred means of providing permissions to instances via IAM roles for things like SSM remote access; this streamlines that experience for users
Amazon is moving to distributing the recommended AMI IDs via SSM Parameters and now this module supports providing just the parameter name in order to pull the appropriate AMI
Both of these changes together make it quite simple and easy to quickly create a secure "bastion" instance using SSM session manager (instead of SSH/PEM keys)

Breaking Changes

No

How Has This Been Tested?

[x] I have updated at least one of the examples/* to demonstrate and validate my change(s)
[x] I have tested and validated these changes using one or more of the provided examples/* projects
[x] I have executed pre-commit run -a on my pull request

This PR is included in version 4.2.0 :tada:

authors: antonbabenko bryantbiggs


text:
Support use of for_each/count parameters

Is your request related to a problem? Please describe.
I'm trying to automate the deployment of n number of identical clusters. It's currently impossible to do so with the EKS module as provider blocks cannot be dynamically provided to a module; they must be statically known at run-time.
Describe the solution you'd like.
When using for_each/count, could the module generate its own provider using parameters given via variables? That way, we wouldn't have to manually specify a provider for each sub-cluster.
Describe alternatives you've considered.
I've considered:

Code generation - works via a bash script or terragrunt, but this involves dependency on documentation or yet another tool
For now, I've gone with duplicating my cluster module 25 times, and using an if statement with count 0 or 1 to enable/disable each cluster. The problem with this is I'm capped at 25 clusters. This is fine since ipv4 subnetting isn't infinitely expandable, but I've now expanded the module to support ipv6 and this lifts such a restriction.

Hi @ajpauwels - this sounds interesting, could you share a little bit more about your use case and outcome you are trying to achieve?

Sure!
I'm investigating having the ability to scale clusters in a single VPC not just vertically (+nodes), but horizontally (+clusters). This is for the following reasons:

In case of desire for increased segregation of services (e.g. a cicd/devops cluster alongside an application-hosting cluster)
In case of desire for multi-tenancy separated by cluster rather than by namespace
In case of desire for cluster-based HA with multiple clusters hosting the same thing and an active-active or active-passive setup

I'm standardizing my cluster setup in a module that sets everything up according to "best practices", and I'd like to be able to instruct the module, with a simple count parameter, to deploy n number of identical clusters, all in one VPC.
I had everything setup how I like it, and it was being deployed fine, but hitting issues when trying to perform the final steps which involve issuing commands to kubernetes API (like updating the aws-auth configmap). This is because each cluster needs an independent kubernetes provider setup to talk with that cluster in particular. This is passed in via a providers block in the module, i.e.
  providers = {
    aws        = aws.cluster
    kubernetes = kubernetes.cluster0
  }

These providers cannot be dynamically generated; this is a Terraform limitation, as Terraform requires the exact providers to be known before planning phase, i.e. the for_each/count parameters are not supported in a provider block.
This effectively makes the EKS module unable to support count/for_each parameters IF the kubernetes API has to be communicated with in the end.
My follow-up questions would therefore be: is it possible to do the full deployment without requiring any communication with the k8s API afterwards? I could potentially setup a separate step that does those separately for me on the cluster group afterwards.
What I've done for now is set a static limit of 25 clusters deployed. I picked 25 clusters due to ipv4 subnetting limitations:

The VPC has one /16 private IP block
An AWS region has at MOST 5 availability zones (most often only 3)
My clusters run one public subnet and one private subnet per AZ
5 * 2 = maximum of 10 subnets per cluster
25 * 10 = 250 /24 subnets
There's an additional 1 subnet per AZ for the hosting of NAT gateways, so for up to 5 AZs, that's up to 5 more /24 subnets, covering a total of 255 potential /24 ipv4 subnets for a full cluster grouping, with one to spare

By having a static maximum, I was able to simply copy the EKS module definition to 25 different files, and add a count parameter to each one that simply determines via 0 or 1 if that cluster will be deployed. This allows me to also have 25 statically defined providers.
However, I've just recently upgraded the cluster definition to support ipv6 networking, which eliminates the subnetting limitation entirely, so I'm revisiting this issue.
I know one of the big no-nos in Terraform module creation is writing a provider block in it when the module is planned to be used as a sub-module. However, in this case, if the provider block for kubernetes (NOT aws, just kubernetes) was written in to this module, using values from both the values and perhaps passed in values (i.e. command/args for customization), then each cluster would have its own provider, and it could remain flexible enough to accomodate all use-cases.

Thank you for sharing - I don't believe there is anything we can do here in this module as its a restriction of Terraform itself. Perhaps the CDKTF might aid in this a bit better - not entirely certain since I don't have first hand experience but that is what I am told

yes @ajpauwels this is a current terraform limitation, you will need to generate those via a wrapper: your own (say bash, python, go), terragrunt, terramate, terraspace, or (as suggested by @bryantbiggs) CDKtf. They each have their pros and cons... which one to choose depends largely on the details of your situation.

@bryantbiggs @schollii Understood, I figured as much. I may explore CDKTF in the future, but for now and for future reference to anyone else viewing this issue, I've amended my bash script to take as a parameter the number of clusters as well. So I have a gen.sh file in my directory that takes some number as its only parameter and will generate cluster01.tf through cluster<number - 1>.tf, based off the file in cluster00.tf. This works fine for my use-case.
Thank you to maintainers for their responses.

authors: ajpauwels bryantbiggs schollii

repo: terraform-aws-modules/terraform-aws-eks


text:
allow_self_assume_role generates errors

Description
I have an issue while creating a simple role with allow_self_assume_role.
Versions

Module version [Required]: 5.5.2

Terraform version:
1.1.2

Provider version(s):

Terraform v1.1.2
on linux_amd64

provider registry.terraform.io/hashicorp/aws v4.36.0

Reproduction Code [Required]

Steps to reproduce the behavior:
provider "aws" {
  region     = "eu-west-2"
}

module "mytest" {
  source  = "terraform-aws-modules/iam/aws//modules/iam-assumable-role"
  version = "~> 5.5"

  trusted_role_services = [
    "ec2.amazonaws.com",
  ]

  allow_self_assume_role = true

  create_role = true

  role_name         = "mytest"
  role_requires_mfa = false

  custom_role_policy_arns           = ["arn:aws:iam::aws:policy/PowerUserAccess", "arn:aws:iam::aws:policy/IAMFullAccess"]
  number_of_custom_role_policy_arns = 2
}

Expected behavior
terraform plan should return no errors
Actual behavior
╷
│ Error: Reference to undeclared local value
│
│   on .terraform/modules/mytest/modules/iam-assumable-role/main.tf line 26, in data "aws_iam_policy_document" "assume_role":
│   26:         values   = ["arn:${local.partition}:iam::${local.account_id}:role${var.role_path}${local.role_name_condition}"]
│
│ A local value with the name "partition" has not been declared.
╵
╷
│ Error: Reference to undeclared local value
│
│   on .terraform/modules/mytest/modules/iam-assumable-role/main.tf line 26, in data "aws_iam_policy_document" "assume_role":
│   26:         values   = ["arn:${local.partition}:iam::${local.account_id}:role${var.role_path}${local.role_name_condition}"]
│
│ A local value with the name "account_id" has not been declared.

I just realised this is the same as #289 . Waiting for that fix.

repo: terraform-aws-modules/terraform-aws-iam


text:
docs: SAM Terraform support is now GA

Description
Update README.md to clarify that SAM support for Terraform is now released

https://aws.amazon.com/blogs/compute/aws-sam-support-for-hashicorp-terraform-now-generally-available/
https://docs.aws.amazon.com/serverless-application-model/latest/developerguide/what-is-terraform-support.html

Motivation and Context

Update outdated information
Encourage usage

Breaking Changes
N/A
How Has This Been Tested?
N/A

This PR is included in version 6.0.1 :tada:

authors: antonbabenko connorads


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chore(deps): update common-dev-assets digest to 54b3d7e

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chore(deps): update ci dependencies

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chore(deps): update module github.com/terraform-ibm-modules/ibmcloud-terratest-wrapper to v1.29.7

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text:
chore: Fix topic name

Description
Repo-bot is throwing validation error for enterpriseDB as well, changing it to now enterprise-db
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authors: Ak-sky terraform-ibm-modules-ops


text:
chore(deps): update ci dependencies

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v1.20.10: DEBUG RELEASE DO NOT USE
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deps: update gomod (#625) (593cd5e)

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deps: update gomod (#620) (06e6aa6)

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revert to old test (#618) (5083b13)

terraform-ibm-modules/common-pipeline-assets (terraform-ibm-modules/common-pipeline-assets)
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update golang test (927e487)

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checkout correct code in common golang pipeline (#538) (1085d82)

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golang pipeline update checkout code (#537) (367334b)

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cbr cleanup (#658) (7721cbe)

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deps: update gomod (#650) (1835de4)

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deps: update gomod (#639) (97a2c5c)

v1.21.0
Features / Fixes

getRemoteURL updated to getRemoteOriginURL for more descriptive name
getSymbolicRef replaced by getCurrentBranch which tries multiple approaches incase one fails on the runtime environment
CleanTerraformDir added the removes terraform metafiles like state, cache and lock files form the target directory
DisableTempWorkingDir added to the test options useful for if you need to keep files around after the test when teardown is disabled
Updated upgrade test to find the upstream URL and origin branch this is to allow a fork to work and have the base branch and repo auto-detected.
Option added for BaseTerraformRepo and BaseTerraformBranch to manually set the base repo and branch for an upgrade test if users are not using a default configuration. These will be overridden by environment variables BASE_TERRAFORM_REPO and BASE_TERRAFORM_BRANCH if set.
Option added DisableTempWorkingDir to disable temporary working directory. Workspace collisions when running in parallel could occur if this is set to true.

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chore(deps): update common-dev-assets digest to 398aa1f

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chore(deps): update module github.com/terraform-ibm-modules/ibmcloud-terratest-wrapper to v1.30.5

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create schematics tar file in correct temp dir (#783) (f0cd2ce)

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chore: name change SKIP UPGRADE TEST

Changing the repo name
Description
Name change for the Liberty SaaS instance, which requires a name change for this repo.
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authors: ChuckCox toddgiguere


text:
feat(deps): update icr.io/ext/sysdig/agent docker tag to v12.19.0

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ci(deps): update terraform-ibm-modules/common-pipeline-assets action to v1.7.1

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add cra scan (#271) (d27aa07)

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text:
feat: watsonx discovery module

Description
This PR addresses the internal Issue to create watson Discovery module.
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created terraform module to provision IBM watson Discovery instance.

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As there is no code yet in main branch yet - so upgrade test will not pass. Skipping it for the initial PR.

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@imprateeksh Can you make same changes you did in WatsonX Assistant PR? Also it looks like Discovery supports Key Protect encryption when you choose the premium plan.
Can you add support for this to the module (it should take in a KMS key CRN, and support creating the s2s auth policy). NOTE: There is no need to take in the KMS instance guid as input - the guid can be parsed from the KMS key CRN. I suggest to add an advanced example which supports creating premium instance, with key protect, and make sure there is a test for it. The upgrade test should use this example.

Sure @ocofaigh - I am already syncing the same suggestions here too.
Regarding the Key protect thing , we are not able to access the Premium plan. Even if I add the KP changes, we will not be able to verify the correctness as we are not able to run the Premium plan. I have provided this info here

@imprateeksh We need to get premium plan access in our account - please find out how. In the meantime, we can proceed with no KMS support until we can test it

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@imprateeksh One small suggestion, it would be good if we can change outputs name as watson_discovery_crn, watson_discovery_... .

@imprateeksh One small suggestion, it would be good if we can change outputs name as watson_discovery_crn, watson_discovery_... .

Referred this - https://github.com/terraform-ibm-modules/terraform-ibm-watsonx-assistant/pull/5#discussion_r1862572657 and now I think we may not need this change for base module. May be for DA. Anyways, ignore for now.

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text:
updated variable names related to watsonx project

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text:
[Bug]: Non-edit bounds for the quest screen are totally wrong, making it unusable

Bug Description
A video explains this best:
https://github.com/terrarium-earth/Heracles/assets/55819817/2b3eaef7-1018-4e8a-a589-5c854ff36292
How to Reproduce?
No response
Expected Behavior
No response
Version
1.0.5
Mod Loader Version
0.20.2
Mod Loader
No response
Logs or additional context
No response
Code of Conduct

[X] I have searched the issue tracker and confirmed that the issue has not been reported
[X] I have checked the FAQ (if one is present) and my issue is not listed
[X] I have verified that I am using the latest version of the mod
[X] I have verified that I have installed all the required dependencies for the mod
[X] I have verified that I do not have Optifine installed. We will close issues if we detect Optifine is in your pack. We cannot fix Optifine issues. Please do not report issues with Optifine present.

The way the sizing works is in edit the size is 500 radius when not editing the bounds are min max -+ 100 so I have no idea how this would happen, and I never ran into it while testing...

Through the magic of a logger!
The Basics: X -52...372 Y -180...164
This should mean that the furthest left quest is X 48, and the furthest right quest is X 272
Here's two basics quests:

So, hmm, the bounds calc is definitely off, right?

Through the magic of an extra logger:
Xs [48, 176, 48, 48, 48, 272, 176, 272, 176]
So, only the visible quests are used, which does make some sense.

That would figure that the bounds are actually pretty correct, but that the way it's being used isn't - that 100 unit buffer should make finders keepers fit comfortably on-screen.

yeah cool i figured it out. it's backwards.

popped a tiny solution it on the end of the other PR, seeing as it's nothing special or proper.

authors: ThatGravyBoat sisby-folk

repo: terrarium-earth/Heracles


text:
SW-3641 Planting zone target planting densities

Track the target planting density (in plants per hectare) for each planting zone.
The value is imported from the shapefile if present; otherwise we use a default.
It can be updated using the admin UI.
Nothing uses this value yet, but it will be an input into planting progress
calculations.

Current dependencies on/for this PR:

main

PR #1171   👈

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@sgrimm started a stack merge that includes this pull request via Graphite.

@sgrimm merged this pull request with Graphite.

repo: terraware/terraware-server


text:
SW-3734 Highlight and Zoom to Zones in Search Results

wondering if we should look into extracting out the visual enhancements into a separate layer from the Map, maybe some sort of hook (not sure on feasibility here).

That's a good thought. I did feel like the map components are getting a bit burdened by this visual stuff. I can think about how extracting them might work out. Thank you

wondering if we should look into extracting out the visual enhancements into a separate layer from the Map, maybe some sort of hook (not sure on feasibility here).

That's a good thought. I did feel like the map components are getting a bit burdened by this visual stuff. I can think about how extracting them might work out. Thank you

Totally, now that we have more advanced requirements that vary across views  - seems like would be a fun thing to rearchitect.

ugh, testing a bit more and finding some bugginess in the way the highlight appears and resets. digging in on this further

I think I'm mostly happy with how the map highlight and focus is working now.

authors: charlie-tf karthikbtf

repo: terraware/terraware-web


text:
Added button with tooltip and used for editting planting sites

#2691  👈
main

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text:
Tessdata on Homebrew

Hello!
I'm working on a project that needs to use the legacy engine (and therefore the legacy language data), but I lack the knowledge to install tessdata instead of tessdata-fast without a Homebrew formula available.
Is there a way to add this tessdata as a Homebrew formula?

It is not necessary to install tessdata instead of tessdata-fast, because both can be installed at the same time, just in different directories to avoid name collisions. My Homebrew installation for example offers all kinds of models:
% ls -l /opt/homebrew/share/tessdata/tessdata*
lrwxr-xr-x  1 sw  admin  34 10 Jan 07:06 /opt/homebrew/share/tessdata/tessdata -> /usr/local/share/tessdata/tessdata
lrwxr-xr-x  1 sw  admin  39 10 Jan 07:06 /opt/homebrew/share/tessdata/tessdata_best -> /usr/local/share/tessdata/tessdata_best
lrwxr-xr-x  1 sw  admin  39 10 Jan 07:06 /opt/homebrew/share/tessdata/tessdata_fast -> /usr/local/share/tessdata/tessdata_fast

So I can run tesseract image.png - -l tessdata/eng --oem 0.
And of course it would be possible to add a Homebrew formula which installs all tessdata models to /opt/homebrew/share/tessdata/tessdata.

Я хотела с пдф вытянуть текст ошибка в том что я заплатила чату GPT с друго аккаунта вообщем почему то так непонимаю хочешь купить а он у вас есть подписка с проплаченная  непонимаю зашла сюда это он мне сказал и что нажала может удалила языки

authors: KaiVinter Liuda-spec stweil

repo: tesseract-ocr/tessdata


text:
tesseract 4.0 is failed to detect less than “<” symbol

Tesseract Version: tesseract 4.0.0-rc2
it extracting <<<<<<<<<<<<<<<<<<<<<<<< symbols as
<KK<KLLLLLLLLLLLLLLLLLLLLLLLRLRK

Please respect guidelines for posting issue.

repo: tesseract-ocr/tesseract


text:
Tesseract4.0 lstmtraining in windows:Load of page 0 failed! Load of images failed!!

Before you submit an issue, please review the guidelines for this repository.
Please report an issue only for a BUG, not for asking questions.
Note that it will be much easier for us to fix the issue if a test case that
reproduces the problem is provided. Ideally this test case should not have any
external dependencies. Provide a copy of the image or link to files for the test case.
Please delete this text and fill in the template below.

Environment

Tesseract Version: tesseract v5.0.0-alpha.20190708
Commit Number:
Platform: Windows, 64-bit

Current Behavior:
lstmtraining --model_output="D:\new_6\output" --continue_from jpn.lstm --train_listfile=text.training_file.txt --traineddata="D:\new_6\jpn.traineddata" -max_iterations 5
Loaded file jpn.lstm, unpacking...
Warning: LSTMTrainer deserialized an LSTMRecognizer!
Continuing from jpn.lstm
Deserialize header failed: D:/new_6/text.font.exp0.lstmf
Load of page 0 failed!
Load of images failed!!
The text.font.exp0.lstmf is spanned by text.font.exp0.tif and text.font.exp0.box, the tif and box file is spanned by text2iamge command.  text.training_file.txt is the path of .lstmf file.

Please create a zip file with your training text, box and tiff files, lstmf file and attach to issue.

new_6.zip

jpn.zip
The file is also in that new_6.zip

I tested just now on ubuntu. It works with following commands. I will check your files and post later.
ubuntu@tesseract-ocr:~/tesstutorial$  ~/tesseract/src/training/tesstrain.sh \
>  --fonts_dir ~/.fonts \
>  --training_text ~/langdata_lstm/jpn/jpn.training_text \
>  --langdata_dir ~/langdata_lstm \
>  --tessdata_dir ~/tessdata_best \
>  --lang jpn \
>  --linedata_only \
>  --noextract_font_properties  \
>  --exposures "0" \
>  --maxpages 3 \
>  --workspace_dir ~/tmp \
>  --save_box_tiff \
>  --fontlist  \
>  "Arial Unicode MS" \
>  --output_dir ~/tesstutorial/jpn_train
Creating new directory /home/ubuntu/tesstutorial/jpn_train

=== Starting training for language 'jpn'
[Wed Jul 31 05:10:37 UTC 2019] /usr/local/bin/text2image --fonts_dir=/home/ubuntu/.fonts --font=Arial Unicode MS --outputbase=/home/ubuntu/tmp/fc-cache/sample_text.txt --text=/home/ubuntu/tmp/fc-cache/sample_text.txt --fontconfig_tmpdir=/home/ubuntu/tmp/fc-cache
Rendered page 0 to file /home/ubuntu/tmp/fc-cache/sample_text.txt.tif

=== Phase I: Generating training images ===
Rendering using Arial Unicode MS
[Wed Jul 31 05:10:39 UTC 2019] /usr/local/bin/text2image --fontconfig_tmpdir=/home/ubuntu/tmp/fc-cache --fonts_dir=/home/ubuntu/.fonts --strip_unrenderable_words --leading=32 --xsize=3600 --char_spacing=0.0 --exposure=0 --outputbase=/tmp/jpn-2019-07-31.sC8/jpn.Arial_Unicode_MS.exp0 --max_pages=3 --font=Arial Unicode MS --text=/home/ubuntu/langdata_lstm/jpn/jpn.training_text
Rendered page 0 to file /tmp/jpn-2019-07-31.sC8/jpn.Arial_Unicode_MS.exp0.tif
Rendered page 1 to file /tmp/jpn-2019-07-31.sC8/jpn.Arial_Unicode_MS.exp0.tif
Rendered page 2 to file /tmp/jpn-2019-07-31.sC8/jpn.Arial_Unicode_MS.exp0.tif

=== Phase UP: Generating unicharset and unichar properties files ===
[Wed Jul 31 05:10:42 UTC 2019] /usr/local/bin/unicharset_extractor --output_unicharset /tmp/jpn-2019-07-31.sC8/jpn.unicharset --norm_mode 1 /tmp/jpn-2019-07-31.sC8/jpn.Arial_Unicode_MS.exp0.box
Extracting unicharset from box file /tmp/jpn-2019-07-31.sC8/jpn.Arial_Unicode_MS.exp0.box
Mirror 〕 of 〔 is not in unicharset
Mirror { of } is not in unicharset
Wrote unicharset file /tmp/jpn-2019-07-31.sC8/jpn.unicharset
[Wed Jul 31 05:10:42 UTC 2019] /usr/local/bin/set_unicharset_properties -U /tmp/jpn-2019-07-31.sC8/jpn.unicharset -O /tmp/jpn-2019-07-31.sC8/jpn.unicharset -X /tmp/jpn-2019-07-31.sC8/jpn.xheights --script_dir=/home/ubuntu/langdata_lstm
Loaded unicharset of size 1405 from file /tmp/jpn-2019-07-31.sC8/jpn.unicharset
Setting unichar properties
Mirror 〕 of 〔 is not in unicharset
Mirror { of } is not in unicharset
Setting script properties
Writing unicharset to file /tmp/jpn-2019-07-31.sC8/jpn.unicharset

=== Phase E: Generating lstmf files ===
Using TESSDATA_PREFIX=/home/ubuntu/tessdata_best
[Wed Jul 31 05:10:43 UTC 2019] /usr/local/bin/tesseract /tmp/jpn-2019-07-31.sC8/jpn.Arial_Unicode_MS.exp0.tif /tmp/jpn-2019-07-31.sC8/jpn.Arial_Unicode_MS.exp0 --psm 6 lstm.train /home/ubuntu/langdata_lstm/jpn/jpn.config
Warning: Parameter not found: textord_tabfind_vertical_horizontal_mix
Warning: Parameter not found: textord_tabfind_vertical_horizontal_mix
Tesseract Open Source OCR Engine v5.0.0-alpha-322-g74ac with Leptonica
Page 1
Page 2
Loaded 46/46 lines (1-46) of document /tmp/jpn-2019-07-31.sC8/jpn.Arial_Unicode_MS.exp0.lstmf
Page 3
Loaded 92/92 lines (1-92) of document /tmp/jpn-2019-07-31.sC8/jpn.Arial_Unicode_MS.exp0.lstmf

=== Constructing LSTM training data ===
[Wed Jul 31 05:10:46 UTC 2019] /usr/local/bin/combine_lang_model --input_unicharset /tmp/jpn-2019-07-31.sC8/jpn.unicharset --script_dir /home/ubuntu/langdata_lstm --words /home/ubuntu/langdata_lstm/jpn/jpn.wordlist --numbers /home/ubuntu/langdata_lstm/jpn/jpn.numbers --puncs /home/ubuntu/langdata_lstm/jpn/jpn.punc --output_dir /home/ubuntu/tesstutorial/jpn_train --lang jpn
Loaded unicharset of size 1405 from file /tmp/jpn-2019-07-31.sC8/jpn.unicharset
Setting unichar properties
Mirror 〕 of 〔 is not in unicharset
Mirror { of } is not in unicharset
Setting script properties
Config file is optional, continuing...
Null char=2
Reducing Trie to SquishedDawg
Reducing Trie to SquishedDawg
Reducing Trie to SquishedDawg

=== Saving box/tiff pairs for training data ===
Moving /tmp/jpn-2019-07-31.sC8/jpn.Arial_Unicode_MS.exp0.box to /home/ubuntu/tesstutorial/jpn_train
Moving /tmp/jpn-2019-07-31.sC8/jpn.Arial_Unicode_MS.exp0.tif to /home/ubuntu/tesstutorial/jpn_train

=== Moving lstmf files for training data ===
Moving /tmp/jpn-2019-07-31.sC8/jpn.Arial_Unicode_MS.exp0.lstmf to /home/ubuntu/tesstutorial/jpn_train

Created starter traineddata for LSTM training of language 'jpn'

Run 'lstmtraining' command to continue LSTM training for language 'jpn'

ubuntu@tesseract-ocr:~/tesstutorial$ rm -rf ~/tesstutorial/jpn_finetune
ubuntu@tesseract-ocr:~/tesstutorial$ mkdir ~/tesstutorial/jpn_finetune
ubuntu@tesseract-ocr:~/tesstutorial$
ubuntu@tesseract-ocr:~/tesstutorial$ combine_tessdata -e ~/tessdata_best/jpn.traineddata ~/tesstutorial/jpn_finetune/jpn.lstm
Extracting tessdata components from /home/ubuntu/tessdata_best/jpn.traineddata
Wrote /home/ubuntu/tesstutorial/jpn_finetune/jpn.lstm
Version string:4.00.00alpha:jpn:synth20170629:[1,48,0,1Ct3,3,16Mp3,3Lfys64Lfx96Lrx96Lfx512O1c1]
0:config:size=2563, offset=192
17:lstm:size=12936715, offset=2755
18:lstm-punc-dawg:size=2602, offset=12939470
19:lstm-word-dawg:size=1167978, offset=12942072
20:lstm-number-dawg:size=50, offset=14110050
21:lstm-unicharset:size=173324, offset=14110100
22:lstm-recoder:size=46601, offset=14283424
23:version:size=80, offset=14330025
ubuntu@tesseract-ocr:~/tesstutorial$
ubuntu@tesseract-ocr:~/tesstutorial$ lstmtraining \
> --model_output ~/tesstutorial/jpn_finetune/jpn_finetune \
> --continue_from ~/tesstutorial/jpn_finetune/jpn.lstm \
> --traineddata ~/tessdata_best/jpn.traineddata \
> --train_listfile ~/tesstutorial/jpn_train/jpn.training_files.txt \
> --debug_interval -1 \
> --max_iterations 400
Loaded file /home/ubuntu/tesstutorial/jpn_finetune/jpn.lstm, unpacking...
Warning: LSTMTrainer deserialized an LSTMRecognizer!
Continuing from /home/ubuntu/tesstutorial/jpn_finetune/jpn.lstm
Loaded 138/138 lines (1-138) of document /home/ubuntu/tesstutorial/jpn_train/jpn.Arial_Unicode_MS.exp0.lstmf
Iteration 0: GROUND  TRUTH : 医療,ざいましたら段々だはのファンNavi '村田東臼杵電力 ケ 使用発射忘れつくる古川居場所検索電機 乃亜。や680 通知酢酸 07価格デジカメ』 。収
Iteration 0: BEST OCR TEXT : 医療.ざいましたら段々だはのファンNavi'村田東臼丁電カケ 使用発射忘れっくる古川居場所検索電機 乃亜。や680 通知酢酸 07価格デジカメ」 。収
File /tmp/jpn-2019-07-31.sC8/jpn.Arial_Unicode_MS.exp0.lstmf line 69 :
Mean rms=0.905%, delta=3.813%, train=11.842%(62.5%), skip ratio=0%
Iteration 1: GROUND  TRUTH : 3600です竹橋住宅。大全ての終了に円September 別3458 が協議粟国 文脈適応 著者蒼い8並ん旬こと紫月 再編こぶ席先進軍声) かつてメーカー ジョ
Iteration 1: BEST OCR TEXT : 3600です竹橋住宅。大全ての終了に円September 別3458 が協議粟国 文脈適応 著者蒼い8並ん旬こと紫月 再編こぶ席先進軍声) かっつてメーカー ジョ
File /home/ubuntu/tesstutorial/jpn_train/jpn.Arial_Unicode_MS.exp0.lstmf line 1 :
Mean rms=0.626%, delta=2.039%, train=6.261%(37.5%), skip ratio=0%
Iteration 2: GROUND  TRUTH : 2850 と! システム] し・バター山口情報 の
File /tmp/jpn-2019-07-31.sC8/jpn.Arial_Unicode_MS.exp0.lstmf line 30 (Perfect):

font.zip
This is the font of word.  Will it work?

Deserialize header failed: D:/new_6/text.font.exp0.lstmf
Load of page 0 failed!
Load of images failed!!

This error is because of the windows EOL.

I am able to run training after changing that. But as I mentioned before (in the other thread) your training text is not correct. You have just made a long list of all characters. The training text needs to be words and punctuation using the characters you want.

I modified your text just to add some spaces and line feed. Here is result for finetune command.
ubuntu@tesseract-ocr:~/tesstutorial$ rm -rf ~/tesstutorial/jpn_finetune
ubuntu@tesseract-ocr:~/tesstutorial$ mkdir ~/tesstutorial/jpn_finetune
ubuntu@tesseract-ocr:~/tesstutorial$
ubuntu@tesseract-ocr:~/tesstutorial$ combine_tessdata -e ~/tessdata_best/jpn.traineddata ~/tesstutorial/jpn_finetune/jpn.lstm
Extracting tessdata components from /home/ubuntu/tessdata_best/jpn.traineddata
Wrote /home/ubuntu/tesstutorial/jpn_finetune/jpn.lstm
Version string:4.00.00alpha:jpn:synth20170629:[1,48,0,1Ct3,3,16Mp3,3Lfys64Lfx96Lrx96Lfx512O1c1]
0:config:size=2563, offset=192
17:lstm:size=12936715, offset=2755
18:lstm-punc-dawg:size=2602, offset=12939470
19:lstm-word-dawg:size=1167978, offset=12942072
20:lstm-number-dawg:size=50, offset=14110050
21:lstm-unicharset:size=173324, offset=14110100
22:lstm-recoder:size=46601, offset=14283424
23:version:size=80, offset=14330025
ubuntu@tesseract-ocr:~/tesstutorial$
ubuntu@tesseract-ocr:~/tesstutorial$ lstmtraining \
> --model_output ~/tesstutorial/jpn_finetune/jpn_finetune \
> --continue_from ~/tesstutorial/jpn_finetune/jpn.lstm \
> --traineddata ~/tessdata_best/jpn.traineddata \
> --train_listfile ~/tesstutorial/jpn_train/jpn.training_files.txt \
> --debug_interval -1 \
> --max_iterations 400
Loaded file /home/ubuntu/tesstutorial/jpn_finetune/jpn.lstm, unpacking...
Warning: LSTMTrainer deserialized an LSTMRecognizer!
Continuing from /home/ubuntu/tesstutorial/jpn_finetune/jpn.lstm
Loaded 94/94 lines (1-94) of document /home/ubuntu/tesstutorial/jpn_train/jpn.Arial_Unicode_MS.exp0.lstmf
Encoding of string failed! Failure bytes: e6 b2 90 e6 b2 99 e6 b2 a1 20 e6 b2 a2 e6 b2 ab e6 b2 b3 20 e6 b2 b8 e6 b2 b9 e6 b2 bb 20 e6 b2 bf e6 b3 81 e6 b3 84 20 e6 b3 89 e6 b3 8a e6 b3 95 20 e6 b3 a1 e6 b3 a2 e6 b3 a3 20 e6 b3 a5 e6 b3 a8 e6 b3 b0 20 e6 b3 b3 e6 b4 8b e6 b4 92 20 e6 b4 97 e6 b4 9e e6 b4 9f 20 e6 b4 a5 e6 b4 aa e6 b4 bb
Can't encode transcription: '沐沙没 沢沫河 沸油治 沿況泄 泉泊法 泡波泣 泥注泰 泳洋洒 洗洞洟 津洪活' in language ''
Loaded 94/94 lines (1-94) of document /home/ubuntu/tesstutorial/jpn_train/jpn.HGMaruGothicMPRO.exp0.lstmf
Encoding of string failed! Failure bytes: e5 af 9e e5 af 9f 20 e5 af a1 e5 af a7 e5 af a9 20 e5 af ae e5 af b5 e5 af b8 20 e5 af ba e5 af be e5 af bf 20 e5 b0 81 e5 b0 82 e5 b0 84 20 e5 b0 86 e5 b0 8a e5 b0 8b 20 e5 b0 8e e5 b0 8f e5 b0 91 20 e5 b0 96 e5 b0 b1 e5 b0 bb 20 e5 b0 bc e5 b0 bd e5 b0 be 20 e5 b0 bf e5 b1 80 e5 b1 81
Can't encode transcription: '寝寞察 寡寧審 寮寵寸 寺対寿 封専射 将尊尋 導小少 尖就尻 尼尽尾 尿局屁' in language ''
Encoding of string failed! Failure bytes: e2 80 95 e2 80 a6 e2 86 92 20 e3 80 81 e3 80 82 e3 80 85 e3 80 87 20 e3 80 8a e3 80 8b e3 80 8c e3 80 8d e3 80 8e e3 80 8f e3 80 90
Can't encode transcription: '!'+,-014 56789:? BCEHL STUacd efilmno prstuy ―…→ 、。々〇 《》「」『』【' in language ''
Encoding of string failed! Failure bytes: e8 aa bc e8 aa bf e8 ab 87 20 e8 ab 8b e8 ab 8d e8 ab 96 20 e8 ab a6 e8 ab ab e8 ab ad 20 e8 ab ae e8 ab b8 e8 ab be 20 e8 ac 80 e8 ac 82 e8 ac 84 20 e8 ac 8e e8 ac 90 e8 ac 99 20 e8 ac 9b e8 ac 9d e8 ac a1 20 e8 ac b3 e8 ac b9 e8 ad 98 20 e8 ad a6 e8 ad ab e8 ad b0
Can't encode transcription: '読誰課 誼調談 請諍論 諦諫諭 諮諸諾 謀謂謄 謎謐謙 講謝謡 謳謹識 警譫議' in language ''
Encoding of string failed! Failure bytes: e7 8b a1 e7 8b a9 20 e7 8b ac e7 8b ad e7 8b bc 20 e7 8b bd e7 8c 9b e7 8c 9d 20 e7 8c 9f e7 8c aa e7 8c ab 20 e7 8c ae e7 8c b6 e7 8c be 20 e7 8c bf e7 8d 84 e7 8d 85 20 e7 8d a3 e7 8d b2 e7 8e 84 20 e7 8e 87 e7 8e 89 e7 8e 8b 20 e7 8e a9 e7 8f 8d e7 8f a0
Can't encode transcription: '狂狐狗 狙狡狩 独狭狼 狽猛猝 猟猪猫 献猶猾 猿獄獅 獣獲玄 率玉王 玩珍珠' in language ''
Encoding of string failed! Failure bytes: e7 9c 87 20 e7 9c 89 e7 9c 8b e7 9c 8c 20 e7 9c 9f e7 9c a0 e7 9c a5 20 e7 9c a9 e7 9c b8 e7 9c ba 20 e7 9c bc e7 9d 80 e7 9d a1 20 e7 9d a3 e7 9d a5 e7 9d a6 20 e7 9d a8 e7 9d ab e7 9e 91 20 e7 9e a0 e7 9e a5 e7 9e ac 20 e7 9e ad e7 9e b0 e7 9e b3
Can't encode transcription: '盲直相 盾省眇 眉看県 真眠眥 眩眸眺 眼着睡 督睥睦 睨睫瞑 瞠瞥瞬 瞭瞰瞳' in language ''
Encoding of string failed! Failure bytes: e9 81 99 20 e9 81 9c e9 81 a0 e9 81 a1 20 e9 81 a3 e9 81 a9 e9 81 ad 20 e9 81 ae e9 81 b5 e9 81 b7 20 e9 81 b8 e9 81 ba e9 81 bf 20 e9 82 84 e9 82 a3 e9 82 aa 20 e9 82 b8 e9 83 81 e9 83 8a 20 e9 83 8e e9 83 a8 e9 83 ad 20 e9 83 b5 e9 83 b7 e9 83 bd 20 e9 84 99 e9 85 8a e9 85 8c
Can't encode transcription: '達違遙 遜遠遡 遣適遭 遮遵遷 選遺避 還那邪 邸郁郊 郎部郭 郵郷都 鄙酊酌' in language ''
Encoding of string failed! Failure bytes: e7 a5 93 e7 a5 96 20 e7 a5 9d e7 a5 9e e7 a5 9f 20 e7 a5 a0 e7 a5 a8 e7 a5 ad 20 e7 a5 b7 e7 a6 81 e7 a6 8d 20 e7 a6 8f e7 a6 bf e7 a7 80 20 e7 a7 81 e7 a7 8b e7 a7 91 20 e7 a7 92 e7 a7 98 e7 a7 a4 20 e7 a7 a9 e7 a7 b0 e7 a7 bb 20 e7 a8 80 e7 a8 8b e7 a8 8e
Can't encode transcription: '祀祈祉 祐祓祖 祝神祟 祠票祭 祷禁禍 福禿秀 私秋科 秒秘秤 秩称移 稀程税' in language ''
Encoding of string failed! Failure bytes: e6 a6 8a e6 a7 8b e6 a7 8c 20 e6 a7 8d e6 a7 98 e6 a7 bd 20 e6 a8 85 e6 a8 8b e6 a8 99 20 e6 a8 a1 e6 a8 a9 e6 a8 aa 20 e6 a8 ab e6 a8 b9 e6 a9 8b 20 e6 a9 9f e6 aa 80 e6 aa 84 20 e6 aa 9c e6 aa bb e6 ab 9b
Can't encode transcription: '植椎検 楠業極 楼楽概 榊構槌 槍様槽 樅樋標 模権横 樫樹橋 機檀檄 檜檻櫛' in language ''
Encoding of string failed! Failure bytes: e5 92 a4 e5 92 ac e5 92 b2 20 e5 92 b3 e5 92 bd e5 93 80 20 e5 93 81 e5 93 84 e5 93 89 20 e5 93 a1 e5 93 ad e5 93 b2 20 e5 94 86 e5 94 87 e5 94 90 20 e5 94 96 e5 94 af e5 94 b1 20 e5 94 b8 e5 94 be e5 95 86 20 e5 95 8f e5 95 93 e5 95 96 20 e5 95 9c e5 95 a3 e5 95 bc 20 e5 96 80 e5 96 84 e5 96 89
Can't encode transcription: '咤咬咲 咳咽哀 品哄哉 員哭哲 唆唇唐 唖唯唱 唸唾商 問啓啖 啜啣啼 喀善喉' in language ''
Encoding of string failed! Failure bytes: e6 ac 92 e6 ac a0 20 e6 ac a1 e6 ac b2 e6 ac ba 20 e6 ac be e6 ad 8c e6 ad 93 20 e6 ad a2 e6 ad a3 e6 ad a4 20 e6 ad a6 e6 ad a9 e6 ad aa 20 e6 ad af e6 ad b3 e6 ad b4 20 e6 ad bb e6 ae 89 e6 ae 8a 20 e6 ae 8b e6 ae 96 e6 ae b2 20 e6 ae b4 e6 ae b5 e6 ae ba 20 e6 ae bb e6 ae bf e6 af 85
Can't encode transcription: '欄欒欠 次欲欺 款歌歓 止正此 武歩歪 歯歳歴 死殉殊 残殖殲 殴段殺 殻殿毅' in language ''
Encoding of string failed! Failure bytes: e5 96 a9 e5 96 aa e5 96 ab 20 e5 96 b0 e5 96 b6 e5 97 84 20 e5 97 85 e5 97 87 e5 97 9a 20 e5 97 9c e5 97 9f e5 97 a4 20 e5 98 86 e5 98 94 e5 98 96 20 e5 98 98 e5 98 a9 e5 98 b2 20 e5 98 b4 e5 99 82 e5 99 8c 20 e5 99 9b e5 99 a4 e5 99 a8
Can't encode transcription: '喋喘喚 喜喝喧 喩喪喫 喰営嗄 嗅嗇嗚 嗜嗟嗤 嘆嘔嘖 嘘嘩嘲 嘴噂噌 噛噤器' in language ''
Encoding of string failed! Failure bytes: e5 b1 8d e5 b1 91 20 e5 b1 93 e5 b1 95 e5 b1 9e 20 e5 b1 a0 e5 b1 a4 e5 b1 a5 20 e5 b1 b1 e5 b1 b9 e5 b2 90 20 e5 b2 a1 e5 b2 a9 e5 b2 b3 20 e5 b2 b8 e5 b3 99 e5 b3 a0 20 e5 b3 b6 e5 b3 bb e5 b4 87 20 e5 b4 8e e5 b4 96 e5 b4 a9 20 e5 b5 8c e5 b5 a9 e5 b6 8b
Can't encode transcription: '居屈届 屋屍屑 屓展属 屠層履 山屹岐 岡岩岳 岸峙峠 島峻崇 崎崖崩 嵌嵩嶋' in language ''
Encoding of string failed! Failure bytes: e8 bc bf e8 bd 84 e8 bd 8d 20 e8 bd a2 e8 be 9b e8 be 9c 20 e8 be 9e e8 be 9f e8 be a3 20 e8 be b0 e8 be b1 e8 be b2 20 e8 be ba e8 be bb e8 be bc 20 e8 be bf e8 bf 82 e8 bf 85 20 e8 bf 8e e8 bf 91 e8 bf 94 20 e8 bf ab e8 bf b0 e8 bf b7
Can't encode transcription: '較載輝 輩輪輸 輿轄轍 轢辛辜 辞辟辣 辰辱農 辺辻込 辿迂迅 迎近返 迫述迷' in language ''
Iteration 0: GROUND  TRUTH : チッツテ デトドナ ニネノハ バパヒビ ピフブプ ヘベペホ ボポマミ ムメモャ ヤュユョヨ ラリルレ
Iteration 0: BEST OCR TEXT : チッツテ デトドナ ニネノハ バパヒビ ピフブプ へベペベペホ ボポマミ ムメモャ ヤュユョヨ ラリルレ
File /tmp/jpn-2019-07-31.AV1/jpn.Arial_Unicode_MS.exp0.lstmf line 20 :

For plusminus type training
ubuntu@tesseract-ocr:~/tesstutorial$ rm -rf ~/tesstutorial/jpn_plusminus
ubuntu@tesseract-ocr:~/tesstutorial$ mkdir ~/tesstutorial/jpn_plusminus
ubuntu@tesseract-ocr:~/tesstutorial$

ubuntu@tesseract-ocr:~/tesstutorial$ combine_tessdata -e ~/tessdata_best/jpn.traineddata ~/tesstutorial/jpn_plusminus/jpn.lstm
Extracting tessdata components from /home/ubuntu/tessdata_best/jpn.traineddata
Wrote /home/ubuntu/tesstutorial/jpn_plusminus/jpn.lstm
Version string:4.00.00alpha:jpn:synth20170629:[1,48,0,1Ct3,3,16Mp3,3Lfys64Lfx96Lrx96Lfx512O1c1]
0:config:size=2563, offset=192
17:lstm:size=12936715, offset=2755
18:lstm-punc-dawg:size=2602, offset=12939470
19:lstm-word-dawg:size=1167978, offset=12942072
20:lstm-number-dawg:size=50, offset=14110050
21:lstm-unicharset:size=173324, offset=14110100
22:lstm-recoder:size=46601, offset=14283424
23:version:size=80, offset=14330025

ubuntu@tesseract-ocr:~/tesstutorial$

ubuntu@tesseract-ocr:~/tesstutorial$ lstmtraining \
> --model_output ~/tesstutorial/jpn_plusminus/jpn_plusminus \
> --continue_from ~/tesstutorial/jpn_plusminus/jpn.lstm \
> --old_traineddata ~/tessdata_best/jpn.traineddata \
> --traineddata ~/tesstutorial/jpn_train/jpn/jpn.traineddata \
> --train_listfile ~/tesstutorial/jpn_train/jpn.training_files.txt \
> --debug_interval -1 \
> --max_iterations 3600

Loaded file /home/ubuntu/tesstutorial/jpn_plusminus/jpn.lstm, unpacking...
Warning: LSTMTrainer deserialized an LSTMRecognizer!
Code range changed from 415 to 364!
Num (Extended) outputs,weights in Series:
  1,48,0,1:1, 0
Num (Extended) outputs,weights in Series:
  C3,3:9, 0
  Ft16:16, 160
Total weights = 160
  [C3,3Ft16]:16, 160
  Mp3,3:16, 0
  Lfys64:64, 20736
  Lfx96:96, 61824
  Lrx96:96, 74112
  Lfx512:512, 1247232
  Fc364:364, 186732
Total weights = 1590796
Previous null char=414 mapped to 363
Continuing from /home/ubuntu/tesstutorial/jpn_plusminus/jpn.lstm
Loaded 94/94 lines (1-94) of document /home/ubuntu/tesstutorial/jpn_train/jpn.Arial_Unicode_MS.exp0.lstmf
Loaded 94/94 lines (1-94) of document /home/ubuntu/tesstutorial/jpn_train/jpn.HGMaruGothicMPRO.exp0.lstmf
Iteration 0: GROUND  TRUTH : 沐沙没 沢沫河 沸油治 沿況泄 泉泊法 泡波泣 泥注泰 泳洋洒 洗洞洟 津洪活
Iteration 0: BEST OCR TEXT : 涼沙没 沢洒河 沸油治 沿況洪 泉泊法 泡波潤 泥注奉 泳洋洒 洗洞尖 津洪活
File /tmp/jpn-2019-07-31.AV1/jpn.Arial_Unicode_MS.exp0.lstmf line 48 :
Mean rms=1.222%, delta=6.162%, train=13.462%(60%), skip ratio=0%
Iteration 1: GROUND  TRUTH : 寝寞察 寡寧審 寮寵寸 寺対寿 封専射 将尊尋 導小少 尖就尻 尼尽尾 尿局屁
Iteration 1: BEST OCR TEXT : 和寝定察 喜寧審 察棚寸 寺対寿 封専射 将尊尋 導小少 汰就避 尼尽尾 尿局慣
File /tmp/jpn-2019-07-31.AV1/jpn.HGMaruGothicMPRO.exp0.lstmf line 3 :
Mean rms=1.283%, delta=6.82%, train=18.269%(55%), skip ratio=0%

I changed the text.font.exp0.txt  add some spaces and line feed, and set .txt and .lstmf to Use utf-8 encoding and unix End of Line characters but show that problem
lstmtraining --model_output="D:\new_6\output" --continue_from jpn.lstm --train_listfile=text.training_file.txt --traineddata="D:\new_6\jpn.traineddata" -max_iterations 5
Loaded file jpn.lstm, unpacking...
Warning: LSTMTrainer deserialized an LSTMRecognizer!
Continuing from jpn.lstm
Loaded 1/1 lines (1-1) of document D:/new_6/text.font.exp0.lstmf
Encoding of string failed! Failure bytes: ffffffe2 ffffff80 ffffff

lstmtraining --model_output="D:\new_6\output" --continue_from jpn.lstm --train_listfile=text.training_file.txt --traineddata="D:\new_6\jpn.traineddata" -max_iterations 5
Loaded file jpn.lstm, unpacking...
Warning: LSTMTrainer deserialized an LSTMRecognizer!
Continuing from jpn.lstm
Deserialize failed: D:/new_6/text.font.exp0.lstmf read 0/538976257 lines
show that：  stop and the cursor is flashing

Could you give me the file which you can training?

Deserialize failed: D:/new_6/text.font.exp0.lstmf read 0/538976257 lines

That is too many lines. Your file has less than 100 lines after I added line breaks.

Here is the zip file. It has the modified training text I used. Please note that it is also not the correct format training text.
Good training text should have correct Japanese Words, numbers, punctuation - similar to files in langdata and langdata_lstm repo.
jpn_train folder has the output files generated by tesstrain.sh using this training text and the font you provided (plus Arial Unicode MS font).
jpn.zip

Thanks, I can train the file to produce  chackpoint file, but during the training that show :
Can't encode transcription: '闄ｉ櫎闄ラ櫚闄甸櫠闄搁櫤闄介殔闅嗛殘闅婇殠闅忛殧闅橀殭闅涢殰闅犻殻闅烽泙闆侀泟闆呴泦闆囬洃 闆㈤洠闆ㄩ洩闆伴洸闆堕浄闆婚渿闇婇湝闇為湩闇查潉闈掗潠闈欓潪闈㈤潻闈撮瀯闉煶闊块爜闋傞爟闋呴爢闋堥爯闋戦爴闋橀牞' in language ''
Iteration 299: GROUND  TRUTH : 銈层偝銈淬偟銈躲偡銈搞偣銈恒偦銈笺偨銈俱偪銉€銉併儍銉勩儐銉囥儓銉夈儕銉嬨儘銉庛儚銉愩儜 銉掋儞銉斻儠銉栥儣銉樸儥銉氥儧銉溿儩銉炪儫銉犮儭銉儯銉ゃ儱銉︺儳銉ㄣ儵銉儷銉儹銉兂銉淬兌銉间竴涓佷竷涓囦笀涓
File D:/new_8/tt.font.exp0.lstmf line 40 (Perfect):
Mean rms=0.025%, delta=0.004%, train=0.041%(1%), skip ratio=4199.33%
2 Percent improvement time=2, best error was 100 @ 0
At iteration 2/300/12898, Mean rms=0.025%, delta=0.004%, char train=0.041%, word train=1%, skip ratio=4199.333%,  New best char error = 0.041 wrote best model:D:\new_8\output0.041_2.checkpoint wrote checkpoint.
Finished! Error rate = 0.041
That influence the training right rate? How can i do for it?

@Shreeshrii  Why when I use the commend ：
tesstrain.sh --fonts_dir /usr/share/fonts --lang eng --linedata_only
--noextract_font_properties --langdata_dir ../langdata
--tessdata_dir ./tessdata --output_dir ~/tesstutorial/trainplusminus
It just open the tesstrain.sh file.

commend:
lstmtraining --model_output="D:\new_9\output_1" continue_from="D:\new_9\jpn.lstm" --old_traineddata="D:\new_9\jpn.traineddata" --traineddata="D:\new_9\jpn.traineddata" --train_listfile="D:\new_9\text.training_file.txt" --debug_innterval -1 max_interations 8
show:
Must provide a --traineddata see training wiki
I have provided the traineddata file ,why it also quest provide a --traineddata?

As mentioned, please see wiki page regarding training.
There are multiple ways for training 4.0. you have to choose the option based on your need or try different ones and use whichever gives you best result.
For plus minus training, you gave to give the old traineddata file and old lstm file and the new 'starter traineddata' file.
You have given same filename for both.

Thanks, I can train the file to produce chackpoint file, but during the training that show :
Can't encode transcription: '闄ｉ櫎闄ラ櫚闄甸櫠闄搁櫤闄介殔闅嗛殘闅婇殠闅忛殧闅橀殭闅涢殰闅犻殻闅烽泙闆侀泟闆呴泦闆囬洃 闆㈤洠闆ㄩ洩闆伴洸闆堕浄闆婚渿闇婇湝闇為湩闇查潉闈掗潠闈欓潪闈㈤潻闈撮瀯闉煶闊块爜闋傞爟闋呴爢闋堥爯闋戦爴闋橀牞' in language ''
Iteration 299: GROUND TRUTH : 銈层偝銈淬偟銈躲偡銈搞偣銈恒偦銈笺偨銈俱偪銉€銉併儍銉勩儐銉囥儓銉夈儕銉嬨儘銉庛儚銉愩儜 銉掋儞銉斻儠銉栥儣銉樸儥銉氥儧銉溿儩銉炪儫銉犮儭銉儯銉ゃ儱銉︺儳銉ㄣ儵銉儷銉儹銉兂銉淬兌銉间竴涓佷竷涓囦笀涓
File D:/new_8/tt.font.exp0.lstmf line 40 (Perfect):
Mean rms=0.025%, delta=0.004%, train=0.041%(1%), skip ratio=4199.33%
2 Percent improvement time=2, best error was 100 @ 0
At iteration 2/300/12898, Mean rms=0.025%, delta=0.004%, char train=0.041%, word train=1%, skip ratio=4199.333%, New best char error = 0.041 wrote best model:D:\new_8\output0.041_2.checkpoint wrote checkpoint.
Finished! Error rate = 0.041
That influence the training right rate? How can i do for it?

@zthdsb Are you still getting these errors?
You have a very high skip ratio - skip ratio=4199.33%
How are you creating the box files?
Your training text sample was one long line without any spaces or line breaks. Have you tried by creating a training text using actual Japanese words?

authors: Shreeshrii zthdsb


text:
Tune Cassandra options for faster startup

We never attempted at tuning Cassandra options to make it start faster. Apparently, there are a few low hanging fruits (focused on single-node scenario) that make it start significantly faster:
Before:
Container cassandra:3.11.2 started in PT32.628781S

After:
Container cassandra:3.11.2 started in PT10.720409S

@kiview yep! (are you also thinking about BitBucket? ;))

repo: testcontainers/testcontainers-java


text:
Disable package installation for all containers by default

Disable package installation for all containers by default as it increases startup time even if you do not use features that require packages to be installed.
You should specify property explicitly: embedded.name-of-container.install.enabled=true for the packages to be installed.

Codecov Report

Merging #164 into develop will not change coverage.
The diff coverage is 0%.

@@            Coverage Diff             @@
##             develop     #164   +/-   ##
==========================================
  Coverage      84.22%   84.22%
  Complexity       378      378
==========================================
  Files            103      103
  Lines           1249     1249
  Branches          13       13
==========================================
  Hits            1052     1052
  Misses           190      190
  Partials           7        7

Impacted Files
Coverage Δ
Complexity Δ

...st/common/properties/InstallPackageProperties.java
0% <0%> (ø)
0 <0> (ø)
:arrow_down:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update b3c4e76...c1e17c4. Read the comment docs.

authors: Aloren codecov-io


text:
Additional issues with Certbot?

There appear to be additional considerations when adding encryption to support https access. Is this addressed elsewhere in your (excellent) work?

Apologies for the late response, @eolach. You would want to set up SSL/TLS to secure Nginx.
https://medium.com/@pentacent/nginx-and-lets-encrypt-with-docker-in-less-than-5-minutes-b4b8a60d3a71

Thanks.
Sent from my iPhone

On Jan 31, 2019, at 7:34 PM, Michael Herman notifications@github.com wrote:
Apologies for the late response, @eolach. You would want to set up SSL/TLS to secure Nginx.
https://medium.com/@pentacent/nginx-and-lets-encrypt-with-docker-in-less-than-5-minutes-b4b8a60d3a71
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub, or mute the thread.

repo: testdrivenio/django-on-docker


text:
docker优化

增加docker-compose 文件，可以通过一行命令
docker-compose up
来启动脚本容器，而不是通过原始的docker build -t . && docker run ***等复杂的命令。
可以通过docker-compose up -d来实现后台抢。需要docker-compose 环境，如果有docker，则只需pip install docker-compose即可，简化环境运行。如果可以建议在requirement.txt加入docker-compose的环境。

晚上我去测试下，感谢

关于docker的问题可以咨询我，我会尽我的能力做出回答。
目前只是针对你做的做了个compose的封装。
不过我发现还有点问题，即:
启动容器后配置文件无法修改的问题。
(因为你一开始是将所有的内容COPY进入到容器中去，所以后期在外头更改了配置文件之后，如更换站点，时间等。即使重启容器也无法更新配置，这样做是不对的。这样的话你的docker 镜像仅仅只是针对其中的一个配置所作的，通用性并不强。）
此种问题可以通过使用文件挂载的方式解决，这样做的好处是即使后期修改配置文件后，直接更新命令就可以重新抢票。更加通用。
可以的话这个周末我会针对这一问题进行解决。

执行docker-compose up经常会报错：
Creating network "12306_default" with the default driver
Creating 12306ticket ... error
ERROR: for 12306ticket  Cannot start service ticket: error while creating mount source path '/host_mnt/d/xxx/12306': mkdir /host_mnt/d: file exists

重启docker和重新build可以解决，但这都太耗时间了，是不是dockerfile有问题？

在windows下执行docker-compose up经常会报错：
Creating network "12306_default" with the default driver
Creating 12306ticket ... error
ERROR: for 12306ticket  Cannot start service ticket: error while creating mount source path '/host_mnt/d/xxx/12306': mkdir /host_mnt/d: file exists

重启docker和重新build可以解决，但这都太耗时间了，是不是dockerfile有问题？

我看了看dockerfile应该没什么问题，也许是因为现在版本升级了，已经是python3了，镜像的基础还是根据python2.7.15来做的。你可以试着升级一下镜像的base版本到python3. 我最近这边没有可用的相关电脑，估计得稍晚才能看看这个问题。

authors: MonsterTan testerSunshine w371987114


text:
Feat[TE-23826] - SSH addon connection and execute multiple commands

JIRA
https://testsigma.atlassian.net/browse/TE-23826
Functionlity
Connects using SSH and Execute multiple commands using terminal

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.

authors: CLAassistant akhil-testsigma

repo: testsigmahq/testsigma-addons


text:
Adjust for API 9

I don't actually know how sigs work. Either before or after API 9, so I mostly just looked at other plugins that had to make similar changes and did the other things I know needed to be done (add I to services that became interfaces).
But testing on my machine, it works!

Oops, I just wrote the same feature and was about to test it before seeing this PR.
Thanks for writing/testing!

repo: tesu/PennyPincher


text:
Cannot change autostart in config

Hello,
I would like to change the autostart option globally, so I added it to the config.yml:
tetranz_select2_entity:
    autostart: false

But:

Unrecognized option "autostart" under "tetranz_select2_entity"

Is it normal?

Yeah, that's "normal" because autostart is not a global setting so for now you'll have to set it per instance.
It probably should be global so I'll try to get to that when I have time but anyone is welcome to submit a P.R.