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RELEASE.md
`DynamicUpdateSlice`. * Enabled a new MLIR-based dynamic range quantization backend by default * The new backend is used for post-training int8 dynamic range quantization and post-training float16 quantization. * Set `experimental_new_dynamic_range_quantizer` in tf.lite.TFLiteConverter to False to disable this change
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tensorflow/c/eager/tape.h
} } // Tell the forward accumulator to watch tensor_id, with a Tensor tangent // vector `tangent` of matching shape and dtype. Tangents are the "vector" in // "Jacobian-vector product"; `Watch`ing a new Tensor and immediately calling // FetchJVP for it would return `tangent`. void Watch(int64_t tensor_id, Gradient* tangent); // Removes the gradient associated with tensor_id. Should be called when the
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tensorflow/c/eager/gradient_checker.cc
namespace tensorflow { namespace gradients { using namespace std; // ================== Helper functions ================= // Fills data with values [start,end) with given step size. void Range(vector<int32_t>* data, int32_t start, int32_t end, int32_t step = 1) { for (int32_t i = start; i < end; i += step) { (*data)[i] = i; } } // Fills out_dims with the dimensions of the given tensor.
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