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.github/ISSUE_TEMPLATE/tflite-other.md
required: true - type: textarea id: code-to-reproduce attributes: label: Standalone code to reproduce the issue description: Provide a reproducible test case that is the bare minimum necessary to generate the problem. If possible, please share a link to Colab/Jupyter/any notebook. placeholder: Tell us what you see! value: render: shell validations: required: true
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.github/ISSUE_TEMPLATE/tflite-op-request.md
**Provide the text output from tflite_convert** ``` # Copy and paste here ``` **Standalone code to reproduce the issue** Provide a reproducible test case that is the bare minimum necessary to generate the problem. If possible, please share a link to Colab/Jupyter/any notebook. Also, please include a link to a GraphDef or the model if possible. **Any other info / logs**
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.github/ISSUE_TEMPLATE/tensorflow_issue_template.yaml
required: true - type: textarea id: code-to-reproduce attributes: label: Standalone code to reproduce the issue description: Provide a reproducible test case that is the bare minimum necessary to generate the problem. Please share a link to Colab, Jupyter, or any notebook. placeholder: Tell us what you see! value: render: shell validations: required: true
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tensorflow/c/eager/c_api_test_util.h
tensorflow::uint64 send_device_incarnation); // Return a 1-D INT32 tensor containing a single value 1. TFE_TensorHandle* TestAxisTensorHandle(TFE_Context* ctx); // Return an op taking minimum of `input` long `axis` dimension. TFE_Op* MinOp(TFE_Context* ctx, TFE_TensorHandle* input, TFE_TensorHandle* axis); // If there is a device of type `device_type`, returns true
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.github/ISSUE_TEMPLATE/tflite-in-play-services.md
- Google Play Services version (`Settings` > `Apps` > `Google Play Services` > `App details`): **Standalone code to reproduce the issue** Provide a reproducible test case that is the bare minimum necessary to generate the problem. If possible, please share a link to or attach code demonstrating the problem. **Any other info / logs** Include any logs or source code that would be helpful to diagnose the problem.
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.bazelrc
# Build with the AVX instruction set when on macOS x86 build:release_macos_x86 --config=avx_linux build:release_macos_x86 --cpu=darwin # Target Catalina as the minimum compatible OS version build:release_macos_x86 --macos_minimum_os=10.15 build:release_macos_x86 --action_env MACOSX_DEPLOYMENT_TARGET=10.15 # Build configs for macOS Arm64 build:release_macos_arm64 --config=release_macos_base
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tensorflow/c/experimental/filesystem/plugins/gcs/ram_file_block_cache.cc
new_entry->timestamp = timer_seconds_(); block_map_.emplace(std::make_pair(key, new_entry)); return new_entry; } // Remove blocks from the cache until we do not exceed our maximum size. void RamFileBlockCache::Trim() { while (!lru_list_.empty() && cache_size_ > max_bytes_) { RemoveBlock(block_map_.find(lru_list_.back())); } }
C++ - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Thu Jul 16 01:39:09 GMT 2020 - 11.1K bytes - Viewed (0) -
tensorflow/c/c_api_experimental.h
// Returns whether the single GPU or general XLA auto jit optimizations are // enabled through MarkForCompilationPassFlags. TF_CAPI_EXPORT unsigned char TF_GetXlaAutoJitEnabled(); // Sets XLA's minimum cluster size. This has global effect. TF_CAPI_EXPORT void TF_SetXlaMinClusterSize(int size); // Gets/Sets TF/XLA flag for whether(true) or not(false) to disable constant
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RELEASE.md
* TensorFlow 1.7 may be the last time we support Cuda versions below 8.0. Starting with TensorFlow 1.8 release, 8.0 will be the minimum supported version. * TensorFlow 1.7 may be the last time we support cuDNN versions below 6.0. Starting with TensorFlow 1.8 release, 6.0 will be the minimum supported version. ## Thanks to our Contributors
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configure.py
default_cc_opt_flags = '/arch:AVX' else: # On all other platforms, no longer use `-march=native` as this can result # in instructions that are too modern being generated. Users that want # maximum performance should compile TF in their environment and can pass # `-march=native` there. # See https://github.com/tensorflow/tensorflow/issues/45744 and duplicates default_cc_opt_flags = '-Wno-sign-compare'
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