Lines Matching refs:tensors

79         tensors = {}
110             tensors[name + "_weights"] = interpreter.get_tensor(detail["index"]).flatten()
124         tensors["output_gate_bias"] = interpreter.get_tensor(1 + time_major_offset).flatten()
125         tensors["cell_gate_bias"] = interpreter.get_tensor(2 + time_major_offset).flatten()
126         tensors["forget_gate_bias"] = interpreter.get_tensor(3 + time_major_offset).flatten()
127         tensors["input_gate_bias"] = interpreter.get_tensor(4 + time_major_offset).flatten()
134         return Lib.op_utils.Generated_data(generated_params, tensors, scales, effective_scales)
137         tensors = {}
173 …tensors["input_gate_hidden_weights"] = np.random.randint(minval, maxval, size=shapes["hidden_weigh…
174 …tensors["forget_gate_hidden_weights"] = np.random.randint(minval, maxval, size=shapes["hidden_weig…
175 …tensors["cell_gate_hidden_weights"] = np.random.randint(minval, maxval, size=shapes["hidden_weight…
176 …tensors["output_gate_hidden_weights"] = np.random.randint(minval, maxval, size=shapes["hidden_weig…
177 …tensors["input_gate_input_weights"] = np.random.randint(minval, maxval, size=shapes["input_weights…
178 …tensors["forget_gate_input_weights"] = np.random.randint(minval, maxval, size=shapes["input_weight…
179 …tensors["cell_gate_input_weights"] = np.random.randint(minval, maxval, size=shapes["input_weights"…
180 …tensors["output_gate_input_weights"] = np.random.randint(minval, maxval, size=shapes["input_weight…
184         tensors["input_gate_bias"] = np.random.randint(minval, maxval, size=shapes["bias"])
185         tensors["forget_gate_bias"] = np.random.randint(minval, maxval, size=shapes["bias"])
186         tensors["cell_gate_bias"] = np.random.randint(minval, maxval, size=shapes["bias"])
187         tensors["output_gate_bias"] = np.random.randint(minval, maxval, size=shapes["bias"])
195         return Lib.op_utils.Generated_data(generated_params, tensors, scales, effective_scales)