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tf.fake_quant_with_min_max_args_gradient(gradients, inputs, min=None, max=None, name=None)

tf.fake_quant_with_min_max_args_gradient(gradients, inputs, min=None, max=None, name=None)

See the guide: Tensor Transformations > Fake quantization

Compute gradients for a FakeQuantWithMinMaxArgs operation.

Args:

  • gradients: A Tensor of type float32. Backpropagated gradients above the FakeQuantWithMinMaxArgs operation.
  • inputs: A Tensor of type float32. Values passed as inputs to the FakeQuantWithMinMaxArgs operation.
  • min: An optional float. Defaults to -6.
  • max: An optional float. Defaults to 6.
  • name: A name for the operation (optional).

Returns:

A Tensor of type float32. Backpropagated gradients below the FakeQuantWithMinMaxArgs operation: gradients * (inputs >= min && inputs <= max).

Defined in tensorflow/python/ops/gen_array_ops.py.

© 2017 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/fake_quant_with_min_max_args_gradient