| /external/libopus/src/ |
| mlp_data.c | 10 static const float weights[450] = { variable
111 weights
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| mlp.h | 36 const float *weights; member in struct:__anon25624
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| /external/tensorflow/tensorflow/contrib/tensor_forest/kernels/v4/ |
| leaf_model_operators_test.cc | 74 std::vector<float> weights = {2.3, 20.3, 1.1}; local
76 new TestableInputTarget(labels, weights, 1));
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| /frameworks/ml/nn/runtime/test/specs/V1_0/ |
| fully_connected_float.mod.py | 19 weights = Parameter("op2", "TENSOR_FLOAT32", "{1, 1}", [2]) variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
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| fully_connected_float_2.mod.py | 19 weights = Parameter("op2", "TENSOR_FLOAT32", "{16, 8}", variable
48 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act_relu).To(out0)
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| fully_connected_float_3.mod.py | 19 weights = Parameter("op2", "TENSOR_FLOAT32", "{1, 2}", [2, 4]) variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
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| fully_connected_float_large.mod.py | 19 weights = Parameter("op2", "TENSOR_FLOAT32", "{1, 5}", [2, 3, 4, 5, 6]) # num_units = 1, input_size = 5 variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
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| fully_connected_float_large_weights_as_inputs.mod.py | 19 weights = Input("op2", "TENSOR_FLOAT32", "{1, 5}") # num_units = 1, input_size = 5 variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
28 weights:
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| fully_connected_float_weights_as_inputs.mod.py | 19 weights = Input("op2", "TENSOR_FLOAT32", "{1, 1}") variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
28 weights: [2],
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| fully_connected_quant8.mod.py | 19 weights = Parameter("op2", "TENSOR_QUANT8_ASYMM", "{1, 1}, 0.5f, 0", [2]) variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
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| fully_connected_quant8_2.mod.py | 19 weights = Parameter("op2", "TENSOR_QUANT8_ASYMM", "{3, 10}, 0.5f, 127", variable
26 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act_relu).To(out0)
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| fully_connected_quant8_large.mod.py | 19 weights = Parameter("op2", "TENSOR_QUANT8_ASYMM", "{1, 5}, 0.2, 0", [10, 20, 20, 20, 10]) # num_units = 1, input_size = 5 variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
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| fully_connected_quant8_large_weights_as_inputs.mod.py | 19 weights = Input("op2", "TENSOR_QUANT8_ASYMM", "{1, 5}, 0.2, 0") # num_units = 1, input_size = 5 variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
28 weights:
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| fully_connected_quant8_weights_as_inputs.mod.py | 19 weights = Input("op2", "TENSOR_QUANT8_ASYMM", "{1, 1}, 0.5f, 0") variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
28 weights: [2],
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| /frameworks/ml/nn/runtime/test/specs/V1_1/ |
| fully_connected_float_2_relaxed.mod.py | 19 weights = Parameter("op2", "TENSOR_FLOAT32", "{16, 8}", variable
48 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act_relu).To(out0)
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| fully_connected_float_4d_simple.mod.py | 23 weights = Parameter("op2", "TENSOR_FLOAT32", "{3, 10}", [ variable
31 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
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| fully_connected_float_4d_simple_relaxed.mod.py | 23 weights = Parameter("op2", "TENSOR_FLOAT32", "{3, 10}", [ variable
31 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
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| fully_connected_float_large_relaxed.mod.py | 19 weights = Parameter("op2", "TENSOR_FLOAT32", "{1, 5}", [2, 3, 4, 5, 6]) # num_units = 1, input_size = 5 variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
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| fully_connected_float_large_weights_as_inputs_relaxed.mod.py | 19 weights = Input("op2", "TENSOR_FLOAT32", "{1, 5}") # num_units = 1, input_size = 5 variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
29 weights:
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| fully_connected_float_relaxed.mod.py | 19 weights = Parameter("op2", "TENSOR_FLOAT32", "{1, 1}", [2]) variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
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| fully_connected_float_weights_as_inputs_relaxed.mod.py | 19 weights = Input("op2", "TENSOR_FLOAT32", "{1, 1}") variable
23 model = model.Operation("FULLY_CONNECTED", in0, weights, bias, act).To(out0)
29 weights: [2],
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| /external/tensorflow/tensorflow/contrib/factorization/python/ops/ |
| gmm.py | 90 Can contain any combination of "w" for weights, "m" for means,
129 def weights(self): member in class:GMM
130 """Returns the cluster weights."""
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| /frameworks/ml/nn/runtime/test/generated/models/ |
| rnn.model.cpp | 11 auto weights = model->addOperand(&type1); local
21 model->addOperation(ANEURALNETWORKS_RNN, {input, weights, recurrent_weights, bias, hidden_state_in, activation_param}, {hidden_state_out, output});
24 {input, weights, recurrent_weights, bias, hidden_state_in},
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| rnn_relaxed.model.cpp | 11 auto weights = model->addOperand(&type1); local
21 model->addOperation(ANEURALNETWORKS_RNN, {input, weights, recurrent_weights, bias, hidden_state_in, activation_param}, {hidden_state_out, output});
24 {input, weights, recurrent_weights, bias, hidden_state_in},
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| rnn_state.model.cpp | 11 auto weights = model->addOperand(&type1); local
21 model->addOperation(ANEURALNETWORKS_RNN, {input, weights, recurrent_weights, bias, hidden_state_in, activation_param}, {hidden_state_out, output});
24 {input, weights, recurrent_weights, bias, hidden_state_in},
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