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ci/official/wheel_test/README.md
init files creation process and is subsequently stored in the wheel file after the build. It also contains a few paths that cannot be directly imported. These paths point to attributes or sub-modules within a module's namespace, but they don't correspond to an actual file or directory on the filesystem. The list of such paths is stored in the packages_for_skip variable and will be skipped during the test.
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tensorflow/c/c_api_test.cc
ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_); } TEST_F(CApiGradientsTest, GradientsPrefix_2ndGradientsAsSubScopeOf1st) { BuildGraphAndAddGradientsWithPrefixes("gradients", "gradients/sub"); ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_); } TEST_F(CApiGradientsTest, GradientsPrefix_PrefixMatchesExistingNodeName) { BuildGraphAndAddGradientsWithPrefixes("Const_0");
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tensorflow/api_template.__init__.py
TensorFlow via the command `import tensorflow as tf`. The primary function of this module is to import all of the public TensorFlow interfaces into a single place. The interfaces themselves are located in sub-modules, as described below. Note that the file `__init__.py` in the TensorFlow source code tree is actually only a placeholder to enable test cases to run. The TensorFlow build replaces
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ci/official/requirements_updater/README.md
It takes in a file with a set of dependencies, and produces a more detailed requirements file for each version, with hashes specified for each dependency required, as well as their sub-dependencies. ### How to update/add requirements By default, the name of the base requirements file is `requirements.in`, but it can be set using the `REQUIREMENTS_FILE_NAME` variable. \ For example: ```
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tensorflow/c/experimental/gradients/math_grad.cc
/* Given upstream grad U and a Sub op A-B, the gradients are: * * dA = U * dB = -U * */ // Grad for A DCHECK(grad_outputs[0]); grad_inputs[0] = grad_outputs[0]; grad_inputs[0]->Ref(); // Grad for B // negate the upstream grad std::string name = "Neg_Sub_Grad_B"; TF_RETURN_IF_ERROR(
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RELEASE.md
* `tf.data`: * Moved option `warm_start` from `tf.data.experimental.OptimizationOptions` to `tf.data.Options`. * `tf.lite`: * `sub_op` and `mul_op` support broadcasting up to 6 dimensions.
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ci/official/wheel_test/test_import_api_packages.py
super().setUp() self.api_packages_v2 = _get_api_packages_v2() # Some paths in the api_packages_path file cannot be directly imported. # These paths may point to attributes or sub-modules within a module's # namespace, but they don't correspond to an actual file # or directory on the filesystem. self.packages_for_skip = [ "tensorflow.distribute.cluster_resolver",
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ci/official/containers/linux_arm64/devel.usertools/squash_testlogs.py
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tensorflow/c/eager/gradient_checker.cc
AbstractTensorHandlePtr fMinus(f_outputs[0]); // Take Difference of both estimates: (f(theta + eps) - f(theta - eps)). TF_RETURN_IF_ERROR( ops::Sub(ctx, fPlus.get(), fMinus.get(), f_outputs, "sub_top")); AbstractTensorHandlePtr fDiff(f_outputs[0]); // Calculate using the difference quotient definition: // (f(theta + eps) - f(theta - eps)) / (2 * eps). TF_RETURN_IF_ERROR(
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tensorflow/c/c_api.h
// * We do not provide TF_OK since it is not strictly necessary and we // are not optimizing for convenience. // * We make assumption that one session has one graph. This should be // fine since we have the ability to run sub-graphs. // * We could allow NULL for some arguments (e.g., NULL options arg). // However since convenience is not a primary goal, we don't do this. // * Devices are not in this API. Instead, they are created/used internally
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