/cmsis-nn-latest/Tests/UnitTest/RefactoredTestGen/Lib/ |
D | op_pad.py | 24 import tf_keras as keras namespace 37 model = keras.models.Sequential() 38 model.add(keras.layers.InputLayer(input_shape=shapes["input_tensor"][1:])) 41 …model.add(keras.layers.ZeroPadding2D(padding=((params["pre_pad_w"], params["post_pad_w"]), (params… 43 …model.add(keras.layers.ZeroPadding2D(padding=((params["pre_pad_h"], params["post_pad_h"]), (params…
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D | op_pooling.py | 24 import tf_keras as keras namespace 36 model = keras.models.Sequential() 37 …model.add(keras.layers.InputLayer(input_shape=shapes["input_tensor"][1:], batch_size=shapes["input… 40 keras.layers.AveragePooling2D(pool_size=(params["filter_h"], params["filter_w"]), 46 keras.layers.MaxPooling2D(pool_size=(params["filter_h"], params["filter_w"]),
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D | op_maximum_minimum.py | 24 import tf_keras as keras namespace 39 tf.keras.backend.clear_session() 48 input_1 = keras.layers.Input(batch_input_shape=input_1_shape) 49 input_2 = keras.layers.Input(batch_input_shape=input_2_shape) 52 model = keras.Model([input_1, input_2], [layer])
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D | op_batch_matmul.py | 24 import tf_keras as keras namespace 39 tf.keras.backend.clear_session() 42 input_lhs = keras.layers.Input(batch_input_shape=input_shape_lhs) 43 input_rhs = keras.layers.Input(batch_input_shape=input_shape_rhs) 46 model = keras.Model([input_lhs, input_rhs], [layer])
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D | op_transpose.py | 25 import tf_keras as keras namespace 40 input_lhs = keras.layers.Input(batch_input_shape=input_shape) 42 model = keras.Model([input_lhs], [layer])
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D | op_fully_connected.py | 26 import keras 206 model = keras.models.Sequential() 208 … keras.layers.InputLayer(input_shape=(params["in_ch"], ), batch_size=params["batch_size"])) 210 …fully_connected_layer = keras.layers.Dense(params["out_ch"], activation=None, use_bias=params["gen…
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D | op_lstm.py | 24 import tf_keras as keras namespace 48 input_layer = keras.layers.Input(shape=(params["time_steps"], params["input_size"]), 56 lstm_layer = keras.layers.LSTM(units=params["hidden_size"], 61 lstm_layer = keras.layers.LSTM(units=params["hidden_size"], 65 model = keras.Model(input_layer, lstm_layer, name="LSTM")
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D | op_conv.py | 22 import keras 190 model = keras.models.Sequential() 192 … model.add(keras.layers.InputLayer(input_shape=input_shape[1:], batch_size=params["batch_size"])) 194 conv_layer = keras.layers.Conv2D(params["out_ch"],
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D | test.py | 34 import keras 204 keras_model.compile(loss=keras.losses.categorical_crossentropy,
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/cmsis-nn-latest/Tests/UnitTest/ |
D | requirements.txt | 22 tf-keras ~= 2.16
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D | pooling_settings.py | 21 import keras 88 model = keras.models.Sequential() 90 model.add(keras.layers.InputLayer(input_shape=input_shape[1:], batch_size=self.batches)) 93 keras.layers.AveragePooling2D(pool_size=(self.filter_y, self.filter_x), 99 keras.layers.MaxPooling2D(pool_size=(self.filter_y, self.filter_x),
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D | add_mul_settings.py | 21 import keras 94 input1 = keras.layers.Input(shape=input_shape[1:]) 95 input2 = keras.layers.Input(shape=input_shape[1:]) 97 layer = keras.layers.Add()([input1, input2]) 99 layer = keras.layers.Multiply()([input1, input2]) 102 out = keras.layers.Lambda(function=lambda x: x)(layer) 103 model = keras.models.Model(inputs=[input1, input2], outputs=out)
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D | softmax_settings.py | 20 import keras 150 model = keras.models.Sequential() 152 model.add(keras.layers.Softmax(input_shape=input_shape))
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D | fully_connected_settings.py | 21 import keras 239 model = keras.models.Sequential() 241 keras.layers.InputLayer(input_shape=(self.y_input * self.x_input * self.input_ch, ), 243 …fully_connected_layer = keras.layers.Dense(self.output_ch, activation=None, use_bias=self.generate…
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D | conv_settings.py | 22 import keras 334 model = keras.models.Sequential() 336 model.add(keras.layers.InputLayer(input_shape=input_shape[1:], batch_size=self.batches)) 338 conv_layer = keras.layers.Conv2D(self.output_ch, 352 … depthwise_layer = keras.layers.DepthwiseConv2D(kernel_size=(self.filter_y, self.filter_x), 365 transposed_conv_layer = keras.layers.Conv2DTranspose(self.output_ch,
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D | lstm_settings.py | 22 import tf_keras as keras namespace 145 input_layer = keras.layers.Input(shape=(self.time_steps, self.number_inputs), 150 lstm_layer = keras.layers.LSTM(units=self.number_units, 154 lstm_layer = keras.layers.LSTM(units=self.number_units, 157 model = keras.Model(input_layer, lstm_layer, name="LSTM")
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D | test_settings.py | 22 import keras 29 import keras 134 os.path.basename(__file__), tf.__version__, keras.__version__)) 456 model.compile(loss=keras.losses.categorical_crossentropy,
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D | README.md | 27 python modules required to run all of the scripts. This will install tensorflow and keras to allow …
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