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Results 31 - 34 of 34 for depthwise_conv_2d (0.22 sec)
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tensorflow/compiler/mlir/lite/schema/schema_generated.h
} inline const char * const *EnumNamesBuiltinOperator() { static const char * const names[208] = { "ADD", "AVERAGE_POOL_2D", "CONCATENATION", "CONV_2D", "DEPTHWISE_CONV_2D", "DEPTH_TO_SPACE", "DEQUANTIZE", "EMBEDDING_LOOKUP", "FLOOR", "FULLY_CONNECTED", "HASHTABLE_LOOKUP", "L2_NORMALIZATION", "L2_POOL_2D",
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 21 18:21:50 UTC 2024 - 1M bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/optimize.cc
// Returns the dimension length of the channel dimension and also the slide // size by each position in the channel dimension accordingly. tfl.conv2d and // tfl.fully_connected has heading channel dimension, but tfl.depthwise_conv2d // has tailing channel dimension. This function is to provide a utility to // create the above information from the op property. static std::pair<int64_t, int64_t> GetBiasDimAndSliceSize(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 102.3K bytes - Viewed (0) -
RELEASE.md
collisions across summary types. * When running on GPU (with cuDNN version 7.6.3 or later),`tf.nn.depthwise_conv2d` backprop to `filter` (and therefore also `tf.keras.layers.DepthwiseConv2D`) now operate deterministically (and `tf.errors.UnimplementedError` is no longer thrown) when op-determinism has
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 730.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
and a filter / kernel tensor of shape `[filter_height, filter_width, in_channels, channel_multiplier]`, containing `in_channels` convolutional filters of depth 1, `depthwise_conv2d` applies a different filter to each input channel (expanding from 1 channel to `channel_multiplier` channels for each), then concatenates the results
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 793K bytes - Viewed (0)