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tensorflow/c/eager/tape.h
// If backward_tape is not null, then this call to Accumulate is the result // of a still-active call to Accumulate which is running operations. We // forward these operations to backward_tape so the outer Accumulate call // 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
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tensorflow/BUILD
"//waymo/ml/cn/...", "//waymo/ml/models/...", ], ) package_group( name = "ndarray_tensor_allow_list", packages = [ "//third_party/py/courier/...", "//third_party/py/tensorfn/...", ], ) # Packages that use private types symbols, until they are exported. # TODO(b/154650521) Remove.
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RELEASE.md
* \*fft\* ops now support dtensors with any layout. Fixed bug in 'fft2d/fft3d', 'ifft2d/ifft3d', 'rfft2d/rfft3d', and 'irfft2d/irfft3d' for sharde input. Refer to this [blog post](https://blog.tensorflow.org/2023/08/distributed-fast-fourier-transform-in-tensorflow.html) for details. * `tf.experimental.strict_mode`
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tensorflow/c/eager/parallel_device/parallel_device_lib.h
// acquires each thread in order (and so only one Execute will schedule // blocking collective operations at a time), and avoids some dynamic // allocation/scheduling. // // TODO(allenl): Keep a map from outer thread to list of inner threads rather // than a single list of threads so aliased nested parallel devices don't // re-use a thread. std::vector<std::unique_ptr<DeviceThread>> device_threads_;
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