Searched refs:MobileNetV2 (Results 1 – 12 of 12) sorted by relevance
| /external/tensorflow/tensorflow/python/keras/benchmarks/saved_model_benchmarks/ |
| D | mobilenet_benchmark_test.py | 28 app = tf.keras.applications.MobileNetV2
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| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.keras.applications.mobilenet_v2.pbtxt | 4 name: "MobileNetV2"
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| D | tensorflow.keras.applications.pbtxt | 120 name: "MobileNetV2"
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| /external/tensorflow/tensorflow/tools/api/golden/v2/ |
| D | tensorflow.keras.applications.mobilenet_v2.pbtxt | 4 name: "MobileNetV2"
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| D | tensorflow.keras.applications.pbtxt | 120 name: "MobileNetV2"
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| /external/tensorflow/tensorflow/python/keras/applications/ |
| D | applications_load_weight_test.py | 54 'mobilenet_v2': (mobilenet_v2, [mobilenet_v2.MobileNetV2]),
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| D | applications_test.py | 53 (mobilenet_v2.MobileNetV2, 1280),
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| D | mobilenet_v2.py | 97 def MobileNetV2(input_shape=None, function
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| /external/XNNPACK/bench/ |
| D | convolution.cc | 1399 static void MobileNetV2(benchmark::internal::Benchmark* b) { in MobileNetV2() function
1979 …BENCHMARK_CAPTURE(xnnpack_convolution_f16, mobilenet_v2, "MobileNet v2")->Apply(MobileNetV2)->UseR…
2004 …BENCHMARK_CAPTURE(xnnpack_convolution_f32, mobilenet_v2, "MobileNet v2")->Apply(MobileNetV2)->UseR…
2029 …BENCHMARK_CAPTURE(xnnpack_convolution_qs8, mobilenet_v2, "MobileNet v2")->Apply(MobileNetV2)->UseR…
2054 …BENCHMARK_CAPTURE(xnnpack_convolution_qu8, mobilenet_v2, "MobileNet v2")->Apply(MobileNetV2)->UseR…
2079 …BENCHMARK_CAPTURE(tflite_convolution_f32, mobilenet_v2, "MobileNet v2")->Apply(MobileNetV2)->UseRe…
2104 …BENCHMARK_CAPTURE(armcl_convolution_f32, mobilenet_v2, "MobileNet v2")->Apply(MobileNetV2)->UseRea…
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| /external/tensorflow/tensorflow/lite/g3doc/tutorials/ |
| D | model_maker_image_classification.ipynb | 302 …"Currently, we support several models such as EfficientNet-Lite* models, MobileNetV2, ResNet50 as…
732 …"This library supports EfficientNet-Lite models, MobileNetV2, ResNet50 by now. [EfficientNet-Lite…
734 …"We could switch model to MobileNetV2 by just setting parameter `model_spec` to `mobilenet_v2_spe…
754 … "Evaluate the newly retrained MobileNetV2 model to see the accuracy and loss in testing data."
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| /external/tensorflow/tensorflow/lite/g3doc/performance/ |
| D | model_optimization.md | 159 <tr><td>MobileNetV2</td><td>Top-1 Accuracy</td><td>0.718</td><td>0.7126</td>
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| /external/tensorflow/tensorflow/lite/java/ovic/ |
| D | README.md | 267 Below are the baseline models (MobileNetV2, MnasNet, and MobileNetV3) used to
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