December 2017
Intermediate to advanced
536 pages
14h 23m
English
Content preview from TensorFlow 1.x Deep Learning Cookbook
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ConvNets in TensorFlow
In TensorFlow, if we want to add a convolutional layer, we will write the following:
tf.nn.conv2d(input, filter, strides, padding, use_cudnn_on_gpu=None, data_format=None, name=None)
The following are the arguments:
- input: A tensor, must be one of the following types: half, float32, float64.
- filter: A tensor, must have the same type as input.
- strides: A list of ints. 1D of length 4. The stride of the sliding window for each dimension of input. Must be in the same order as the dimension specified with format.
- padding: A string from: SAME, VALID. The type of padding algorithm to use.
- use_cudnn_on_gpu: An optional bool. Defaults to True.
- data_format: An optional string from: NHWC and NCHW. Defaults to NHWC. Specifies ...
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