Python tensorflow.python.ops.array_ops.strided_slice_grad() Examples

The following are 8 code examples of tensorflow.python.ops.array_ops.strided_slice_grad(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module tensorflow.python.ops.array_ops , or try the search function .
Example #1
Source File: array_grad.py    From lambda-packs with MIT License 6 votes vote down vote up 
def _StridedSliceGrad(op, grad):
  """Gradient for StridedSlice op."""
  x = array_ops.shape(op.inputs[0])
  begin = op.inputs[1]
  end = op.inputs[2]
  strides = op.inputs[3]

  return array_ops.strided_slice_grad(
      x,
      begin,
      end,
      strides,
      grad,
      begin_mask=op.get_attr("begin_mask"),
      end_mask=op.get_attr("end_mask"),
      ellipsis_mask=op.get_attr("ellipsis_mask"),
      new_axis_mask=op.get_attr("new_axis_mask"),
      shrink_axis_mask=op.get_attr("shrink_axis_mask")), None, None, None
Example #2
Source File: array_grad.py    From auto-alt-text-lambda-api with MIT License 6 votes vote down vote up 
def _StridedSliceGrad(op, grad):
  """Gradient for StridedSlice op."""
  x = array_ops.shape(op.inputs[0])
  begin = op.inputs[1]
  end = op.inputs[2]
  strides = op.inputs[3]

  return array_ops.strided_slice_grad(
      x,
      begin,
      end,
      strides,
      grad,
      begin_mask=op.get_attr("begin_mask"),
      end_mask=op.get_attr("end_mask"),
      ellipsis_mask=op.get_attr("ellipsis_mask"),
      new_axis_mask=op.get_attr("new_axis_mask"),
      shrink_axis_mask=op.get_attr("shrink_axis_mask")), None, None, None
Example #3
Source File: array_grad.py    From deep_image_model with Apache License 2.0 6 votes vote down vote up 
def _StridedSliceGrad(op, grad):
  """Gradient for StridedSlice op."""
  x = array_ops.shape(op.inputs[0])
  begin = op.inputs[1]
  end = op.inputs[2]
  strides = op.inputs[3]

  return array_ops.strided_slice_grad(
      x,
      begin,
      end,
      strides,
      grad,
      begin_mask=op.get_attr("begin_mask"),
      end_mask=op.get_attr("end_mask"),
      ellipsis_mask=op.get_attr("ellipsis_mask"),
      new_axis_mask=op.get_attr("new_axis_mask"),
      shrink_axis_mask=op.get_attr("shrink_axis_mask")), None, None, None
Example #4
Source File: array_grad.py    From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License 6 votes vote down vote up 
def _StridedSliceGrad(op, grad):
  """Gradient for StridedSlice op."""
  x = array_ops.shape(op.inputs[0])
  begin = op.inputs[1]
  end = op.inputs[2]
  strides = op.inputs[3]

  return array_ops.strided_slice_grad(
      x,
      begin,
      end,
      strides,
      grad,
      begin_mask=op.get_attr("begin_mask"),
      end_mask=op.get_attr("end_mask"),
      ellipsis_mask=op.get_attr("ellipsis_mask"),
      new_axis_mask=op.get_attr("new_axis_mask"),
      shrink_axis_mask=op.get_attr("shrink_axis_mask")), None, None, None
Example #5
Source File: array_grad.py    From keras-lambda with MIT License 6 votes vote down vote up 
def _StridedSliceGrad(op, grad):
  """Gradient for StridedSlice op."""
  x = array_ops.shape(op.inputs[0])
  begin = op.inputs[1]
  end = op.inputs[2]
  strides = op.inputs[3]

  return array_ops.strided_slice_grad(
      x,
      begin,
      end,
      strides,
      grad,
      begin_mask=op.get_attr("begin_mask"),
      end_mask=op.get_attr("end_mask"),
      ellipsis_mask=op.get_attr("ellipsis_mask"),
      new_axis_mask=op.get_attr("new_axis_mask"),
      shrink_axis_mask=op.get_attr("shrink_axis_mask")), None, None, None
Example #6
Source File: array_ops_test.py    From deep_image_model with Apache License 2.0 5 votes vote down vote up 
def testHostVsDevice(self):
    with self.test_session(use_gpu=True) as sess:
      var2 = tf.Variable(
          tf.reshape(
              tf.cast(tf.range(1, 5, 1), tf.float32), shape=(4, 1, 1)))
      varshape = tf.Variable([6, 4, 4], dtype=tf.int32)
      sess.run(tf.global_variables_initializer())
      begin = tf.constant([0, 0, 0])
      end = tf.constant([4, 1, 1])
      strides = tf.constant([1, 1, 1])
      foo = array_ops.strided_slice_grad(varshape, begin, end, strides, var2)
      sess.run(foo)
Example #7
Source File: array_ops_test.py    From deep_image_model with Apache License 2.0 5 votes vote down vote up 
def testInt64Shape(self):
    with self.test_session(use_gpu=True) as sess:
      original_dy = tf.reshape(
          tf.cast(tf.range(1, 5, 1), tf.float32), shape=(4, 1, 1))
      original_shape = tf.constant([6, 4, 4], dtype=tf.int64)
      sess.run(tf.global_variables_initializer())
      begin = tf.constant([0, 0, 0], dtype=tf.int64)
      end = tf.constant([4, 1, 1], dtype=tf.int64)
      strides = tf.constant([1, 1, 1], dtype=tf.int64)
      dx = array_ops.strided_slice_grad(original_shape, begin, end, strides,
                                        original_dy)
      sess.run(dx)
Example #8
Source File: array_ops_test.py    From deep_image_model with Apache License 2.0 5 votes vote down vote up 
def testMixedIndexTypes(self):
    with self.test_session(use_gpu=True) as sess:
      original_dy = tf.reshape(
          tf.cast(tf.range(1, 5, 1), tf.float32), shape=(4, 1, 1))
      original_shape = tf.constant([6, 4, 4], dtype=tf.int64)
      sess.run(tf.global_variables_initializer())
      begin = tf.constant([0, 0, 0], dtype=tf.int32)
      end = tf.constant([4, 1, 1], dtype=tf.int64)
      strides = tf.constant([1, 1, 1], dtype=tf.int64)
      with self.assertRaisesRegexp(
          TypeError, "Input 'begin' of 'StridedSliceGrad' Op has type int32"
          " that does not match type int64 of argument 'shape'"):
        dx = array_ops.strided_slice_grad(original_shape, begin, end, strides,
                                          original_dy)
        sess.run(dx)