| /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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