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CONTRIBUTING.md
- If all looks good, the reviewer will approve the PR. - If a change is needed, the contributor is requested to make the suggested change. - You make the change and submit it for the review again. - This cycle repeats itself until the PR gets approved. - Note: As a friendly reminder, we may reach out to you if the PR is awaiting your response for more than 2 weeks. **4. Approved**
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.github/workflows/arm-ci.yml
if: github.repository == 'tensorflow/tensorflow' && (github.event.action != 'labeled' || (github.event.action == 'labeled' && github.event.label.name == 'kokoro:force-run')) runs-on: [self-hosted, linux, ARM64] strategy: matrix: pyver: ['3.10'] steps: - name: Stop old running containers (if any) shell: bash run: |
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tensorflow/c/env.h
// Deletes the specified directory and all subdirectories and files underneath // it. This is accomplished by traversing the directory tree rooted at dirname // and deleting entries as they are encountered. // // If dirname itself is not readable or does not exist, *undeleted_dir_count is // set to 1, *undeleted_file_count is set to 0 and an appropriate status (e.g. // TF_NOT_FOUND) is returned. //
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tensorflow/c/eager/parallel_device/parallel_device_testlib.cc
if (TF_GetCode(status) != TF_OK) return; int num_retvals = 0; TFE_Execute(op.get(), nullptr, &num_retvals, status); if (TF_GetCode(status) != TF_OK) return; // Delete the variable handle itself. TFE_DeleteTensorHandle(handle_); } TensorHandlePtr Variable::Read(TFE_Context* context, TF_Status* status) { std::unique_ptr<TFE_Op, decltype(&TFE_DeleteOp)> op(
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tensorflow/c/eager/tape.h
// can do its work. // // Rather than re-entering and delegating Accumulate like this, we could // instead allow ForwardAccumulator some control over the current tape set // (so it can deactivate itself and activate its GradientTape). Currently // that is managed by the language binding and would require relatively // messy callbacks. call_state_.top().backward_tape->RecordOperation(
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ci/official/containers/linux_arm64/builder.devtoolset/stringop_trunc.patch
- && *__s != __accept3) - ++__s; - return *__s == '\0' ? NULL : (char *) (size_t) __s; -} -#endif - - -/* Find the first occurrence of NEEDLE in HAYSTACK. Newer gcc versions - do this itself. */ -#if !defined _HAVE_STRING_ARCH_strstr && !__GNUC_PREREQ (2, 97) -# define strstr(haystack, needle) \ - (__extension__ (__builtin_constant_p (needle) && __string2_1bptr_p (needle) \
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tensorflow/c/eager/parallel_device/parallel_device_lib.cc
} }; using ExecutorPtr = std::unique_ptr<TFE_Executor, ExecutorDeleter>; } // namespace // Allows a single op at a time to be launched without blocking. // // DeviceThread itself is thread-safe, in that StartExecute will block if there // is a pending execution. Since StartExecute is equivalent to grabbing a lock, // multiple DeviceThreads should always be accessed in the same order to avoid // deadlocks.
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.github/workflows/arm-ci-extended-cpp.yml
tags: - v2.** schedule: - cron: '0 2 * * *' permissions: contents: read jobs: build: if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks runs-on: [self-hosted, linux, ARM64] strategy: matrix: pyver: ['3.10'] steps: - name: Stop old running containers (if any) shell: bash run: |
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.github/workflows/arm-cd.yml
branches: - r2.** schedule: - cron: '0 8 * * *' permissions: contents: read jobs: build: if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks runs-on: [self-hosted, linux, ARM64] strategy: fail-fast: false matrix: pyver: ['3.9', '3.10', '3.11', '3.12'] steps: - name: Stop old running containers (if any) shell: bash
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RELEASE.md
StandardizedConv2D(tf.keras.layers.Conv2D): def call(self, inputs): mean, var = tf.nn.moments(self.kernel, axes=[0, 1, 2], keepdims=True) return self.convolution_op(inputs, (self.kernel - mean) / tf.sqrt(var + 1e-10))` Alternatively, you can override `convolution_op`: `python class StandardizedConv2D(tf.keras.Layer): def convolution_op(self, inputs,
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