本文整理汇总了Python中tensorflow.python.ops.nn_ops.conv2d_backprop_filter函数的典型用法代码示例。如果您正苦于以下问题：Python conv2d_backprop_filter函数的具体用法？Python conv2d_backprop_filter怎么用？Python conv2d_backprop_filter使用的例子？那么恭喜您, 这里精选的函数代码示例或许可以为您提供帮助。
在下文中一共展示了conv2d_backprop_filter函数的7个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: testGradientDilatedConv
def testGradientDilatedConv(self):
if test.is_gpu_available(cuda_only=True):
with self.test_session(use_gpu=True):
for padding in ["SAME", "VALID"]:
for stride in [1, 2]:
np.random.seed(1)
in_shape = [5, 8, 6, 4]
in_val = constant_op.constant(
2 * np.random.random_sample(in_shape) - 1, dtype=dtypes.float32)
filter_shape = [3, 3, 4, 6]
# Make a convolution op with the current settings,
# just to easily get the shape of the output.
conv_out = nn_ops.conv2d(
in_val,
array_ops.zeros(filter_shape),
dilations=[1, 2, 2, 1],
strides=[1, stride, stride, 1],
padding=padding)
out_backprop_shape = conv_out.get_shape().as_list()
out_backprop_val = constant_op.constant(
2 * np.random.random_sample(out_backprop_shape) - 1,
dtype=dtypes.float32)
output = nn_ops.conv2d_backprop_filter(
in_val,
filter_shape,
out_backprop_val,
dilations=[1, 2, 2, 1],
strides=[1, stride, stride, 1],
padding=padding)
err = gradient_checker.compute_gradient_error(
[in_val, out_backprop_val], [in_shape, out_backprop_shape],
output, filter_shape)
print("conv2d_backprop_filter gradient err = %g " % err)
err_tolerance = 2e-3
self.assertLess(err, err_tolerance)示例2: _Conv2DBackpropInputGrad
def _Conv2DBackpropInputGrad(op, grad):
"""The derivatives for deconvolution.
Args:
op: the Deconvolution op.
grad: the tensor representing the gradient w.r.t. the output
Returns:
the gradients w.r.t. the input and the filter
"""
return [
None,
nn_ops.conv2d_backprop_filter(
grad,
array_ops.shape(op.inputs[1]),
op.inputs[2],
dilations=op.get_attr("dilations"),
strides=op.get_attr("strides"),
padding=op.get_attr("padding"),
use_cudnn_on_gpu=op.get_attr("use_cudnn_on_gpu"),
data_format=op.get_attr("data_format").decode()),
nn_ops.conv2d(
grad,
op.inputs[1],
dilations=op.get_attr("dilations"),
strides=op.get_attr("strides"),
padding=op.get_attr("padding"),
use_cudnn_on_gpu=op.get_attr("use_cudnn_on_gpu"),
data_format=op.get_attr("data_format").decode())
]示例3: _Conv2DGrad
def _Conv2DGrad(op, grad):
dilations = op.get_attr("dilations")
strides = op.get_attr("strides")
padding = op.get_attr("padding")
use_cudnn_on_gpu = op.get_attr("use_cudnn_on_gpu")
data_format = op.get_attr("data_format")
shape_0, shape_1 = array_ops.shape_n([op.inputs[0], op.inputs[1]])
return [
nn_ops.conv2d_backprop_input(
shape_0,
op.inputs[1],
grad,
dilations=dilations,
strides=strides,
padding=padding,
use_cudnn_on_gpu=use_cudnn_on_gpu,
data_format=data_format),
nn_ops.conv2d_backprop_filter(
op.inputs[0],
shape_1,
grad,
dilations=dilations,
strides=strides,
padding=padding,
use_cudnn_on_gpu=use_cudnn_on_gpu,
data_format=data_format)
]示例4: _Conv2DGrad
def _Conv2DGrad(op, grad):
return [
nn_ops.conv2d_backprop_input(
array_ops.shape(op.inputs[0]), op.inputs[1], grad, op.get_attr("strides"), op.get_attr("padding")
),
nn_ops.conv2d_backprop_filter(
op.inputs[0], array_ops.shape(op.inputs[1]), grad, op.get_attr("strides"), op.get_attr("padding")
),
]示例5: testBackwardFilterGradient
def testBackwardFilterGradient(self):
np.random.seed(1)
in_shape = LayerShape(batch=8, height=128, width=128, channels=8)
filter_shape = FilterShape(height=3, width=3, in_channels=8, out_channels=8)
in_op = self._random_data_op(in_shape)
out_op = self._random_out_op(in_shape, filter_shape)
filter_gradient_op = nn_ops.conv2d_backprop_filter(
in_op, filter_shape, out_op, strides=_STRIDES, padding=_PADDING)
self._assert_reproducible(filter_gradient_op)示例6: _DeConv2DGrad
def _DeConv2DGrad(op, grad):
"""The derivatives for deconvolution.
Args:
op: the Deconvolution op.
grad: the tensor representing the gradient w.r.t. the output
Returns:
the gradients w.r.t. the input and the filter
"""
return [
None,
nn_ops.conv2d_backprop_filter(
grad, array_ops.shape(op.inputs[1]), op.inputs[2], op.get_attr("strides"), op.get_attr("padding")
),
nn_ops.conv2d(grad, op.inputs[1], op.get_attr("strides"), op.get_attr("padding")),
]示例7: _Conv2DGrad
def _Conv2DGrad(op, grad):
return [
nn_ops.conv2d_backprop_input(
array_ops.shape(op.inputs[0]),
op.inputs[1],
grad,
op.get_attr("strides"),
op.get_attr("padding"),
op.get_attr("use_cudnn_on_gpu"),
op.get_attr("data_format"),
),
nn_ops.conv2d_backprop_filter(
op.inputs[0],
array_ops.shape(op.inputs[1]),
grad,
op.get_attr("strides"),
op.get_attr("padding"),
op.get_attr("use_cudnn_on_gpu"),
op.get_attr("data_format"),
),
]