Lines Matching refs:params
28 def get_shapes(params): argument
30 if params["time_major"] and params["tflite_generator"] == "json":
31 shapes["input"] = (params["time_steps"], params["batch_size"], params["input_size"])
33 shapes["input"] = (params["batch_size"], params["time_steps"], params["input_size"])
35 shapes["input_weights"] = (params["input_size"], params["hidden_size"])
36 shapes["all_input_weights"] = (params["input_size"], params["hidden_size"] * 4)
38 shapes["hidden_weights"] = (params["hidden_size"], params["hidden_size"])
39 shapes["all_hidden_weights"] = (params["hidden_size"], params["hidden_size"] * 4)
41 shapes["bias"] = (1, params["hidden_size"])
42 shapes["all_bias"] = (params["hidden_size"] * 4, )
44 …shapes["representational_dataset"] = (params["batch_size"], params["time_steps"], params["input_si…
47 def generate_keras_model(shapes, params): argument
48 input_layer = keras.layers.Input(shape=(params["time_steps"], params["input_size"]),
49 batch_size=params["batch_size"],
53 if params["time_major"]:
56 lstm_layer = keras.layers.LSTM(units=params["hidden_size"],
57 time_major=params["time_major"],
61 lstm_layer = keras.layers.LSTM(units=params["hidden_size"],
62 time_major=params["time_major"],
78 def generate_data_tflite(tflite_fname, params): argument
88 if params["time_major"]:
136 def generate_data_json(shapes, params): argument
171 minval = Lib.op_utils.get_dtype_min(params["weights_data_type"])
172 maxval = Lib.op_utils.get_dtype_max(params["weights_data_type"])
182 maxval = Lib.op_utils.get_dtype_max(params["input_data_type"])
189 minval = Lib.op_utils.get_dtype_min(params["input_data_type"])
190 maxval = Lib.op_utils.get_dtype_max(params["input_data_type"])