| /external/tensorflow/tensorflow/lite/delegates/xnnpack/ |
| D | depthwise_conv_2d_test.cc | 28 TEST(DepthwiseConv2D, 1x1) {
49 TEST(DepthwiseConv2D, 2x2) {
71 TEST(DepthwiseConv2D, 3x3) {
93 TEST(DepthwiseConv2D, 3x3Stride2) {
117 TEST(DepthwiseConv2D, 5x5) {
139 TEST(DepthwiseConv2D, 5x5Stride2) {
163 TEST(DepthwiseConv2D, SmallKernelWithSamePadding) { in TEST() argument
190 TEST(DepthwiseConv2D, SmallKernelWithValidPadding) { in TEST() argument
217 TEST(DepthwiseConv2D, StrideWithSamePadding) { in TEST() argument
248 TEST(DepthwiseConv2D, StrideWithValidPadding) { in TEST() argument
[all …]
|
| /external/tensorflow/tensorflow/lite/micro/kernels/vexriscv/doc/ |
| D | DepthwiseConv2D_int8.md | 1 # Design of DepthwiseConv2D for VexRISCV
29 among the models deployed on edge devices: DepthwiseConv2D (see
30 [TensorFlow Python API](https://www.tensorflow.org/api_docs/python/tf/keras/layers/DepthwiseConv2D);
65 with DepthwiseConv2D layers using TensorFlow Lite Micro will benefit from this
88 beneficial to implement DepthwiseConv2D in a depth-centric manner, namely,
100 * Relating sequential memory access to DepthwiseConv2D
103 ### Relating sequential memory access to DepthwiseConv2D
|
| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.keras.layers.-depthwise-conv2-d.pbtxt | 1 path: "tensorflow.keras.layers.DepthwiseConv2D"
3 is_instance: "<class \'tensorflow.python.keras.layers.convolutional.DepthwiseConv2D\'>"
|
| D | tensorflow.keras.layers.pbtxt | 152 name: "DepthwiseConv2D"
|
| /external/tensorflow/tensorflow/tools/api/golden/v2/ |
| D | tensorflow.keras.layers.-depthwise-conv2-d.pbtxt | 1 path: "tensorflow.keras.layers.DepthwiseConv2D"
3 is_instance: "<class \'tensorflow.python.keras.layers.convolutional.DepthwiseConv2D\'>"
|
| D | tensorflow.keras.layers.pbtxt | 144 name: "DepthwiseConv2D"
|
| /external/tensorflow/tensorflow/lite/micro/kernels/vexriscv/ |
| D | README.md | 49 * [DepthwiseConv2D](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/micro/ke…
|
| /external/tensorflow/tensorflow/lite/g3doc/guide/ |
| D | ops_version.md | 167 we implemented a new op kernel which can handle `DepthwiseConv2D` version 1 and
220 `DepthwiseConv2D`:
|
| /external/tensorflow/tensorflow/lite/delegates/hexagon/ |
| D | README.md | 71 * DepthwiseConv2D:
|
| /external/tensorflow/tensorflow/python/keras/mixed_precision/ |
| D | layer_correctness_test.py | 89 ('DepthwiseConv2D', lambda: convolutional.DepthwiseConv2D(2, 2),
|
| /external/tensorflow/tensorflow/python/keras/applications/ |
| D | mobilenet.py | 418 x = layers.DepthwiseConv2D((3, 3),
|
| D | mobilenet_v2.py | 449 x = layers.DepthwiseConv2D(
|
| D | efficientnet.py | 468 x = layers.DepthwiseConv2D(
|
| D | mobilenet_v3.py | 518 x = layers.DepthwiseConv2D(
|
| D | resnet.py | 402 x = layers.DepthwiseConv2D(
|
| /external/tensorflow/tensorflow/python/keras/benchmarks/layer_benchmarks/ |
| D | layer_benchmarks_test.py | 111 ("DepthwiseConv2D_small_shape", tf.keras.layers.DepthwiseConv2D,
|
| /external/tensorflow/tensorflow/lite/delegates/coreml/ |
| D | README.md | 73 * DepthwiseConv2D
|
| /external/tensorflow/tensorflow/compiler/mlir/lite/transforms/ |
| D | prepare_patterns.td | 131 [(UsedBy<"DepthwiseConv2D"> $old_value)], (addBenefit 10)>;
|
| /external/tensorflow/tensorflow/python/keras/layers/ |
| D | __init__.py | 103 from tensorflow.python.keras.layers.convolutional import DepthwiseConv2D
|
| D | convolutional.py | 2258 class DepthwiseConv2D(Conv2D): class
2362 super(DepthwiseConv2D, self).__init__(
2461 config = super(DepthwiseConv2D, self).get_config()
|
| D | convolutional_test.py | 1157 keras.layers.DepthwiseConv2D,
|
| /external/tensorflow/tensorflow/lite/g3doc/performance/ |
| D | coreml_delegate.md | 250 * DepthwiseConv2D
|
| /external/tensorflow/tensorflow/core/kernels/mkl/ |
| D | mkl_quantized_conv_ops_test.cc | 642 TEST_F(QuantizedConv2DTest, DepthwiseConv2D) { in TEST_F() argument
|
| /external/tensorflow/tensorflow/compiler/mlir/tosa/transforms/ |
| D | legalize_tfl.cc | 107 DECL_CONVERT_OP(DepthwiseConv2D);
|