| /packages/modules/NeuralNetworks/runtime/test/specs/V1_2/ |
| D | unidirectional_sequence_rnn.mod.py | 21 recurrent_weights_data, bias_data, hidden_state_data, output_data): argument
113 output_data = [ variable
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| D | exp.mod.py | 24 output_data = [math.exp(x) for x in input_data] variable
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| D | sqrt.mod.py | 24 output_data = [math.sqrt(x) for x in input_data] variable
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| D | abs.mod.py | 22 output_data = [abs(x) for x in input_data] variable
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| D | sin.mod.py | 24 output_data = [math.sin(x) for x in input_data] variable
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| D | neg.mod.py | 22 output_data = [-x for x in input_data] variable
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| D | log.mod.py | 24 output_data = [math.log(x) for x in input_data] variable
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| D | rsqrt.mod.py | 24 output_data = [1.0 / math.sqrt(x) for x in input_data] variable
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| D | reduce_all.mod.py | 17 def test(input0, output0, axes, keep_dims, input_data, output_data): argument
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| D | reduce_max.mod.py | 17 def test(input0, output0, axes, keep_dims, input_data, output_data): argument
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| D | reduce_any.mod.py | 17 def test(input0, output0, axes, keep_dims, input_data, output_data): argument
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| D | log_softmax.mod.py | 19 def test(input0, output0, input_data, beta, axis, output_data): argument
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| D | reduce_sum.mod.py | 17 def test(input0, output0, axes, keep_dims, input_data, output_data): argument
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| D | gather.mod.py | 17 def test(input0, axis, indices, output0, input_data, output_data): argument
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| D | reduce_prod.mod.py | 17 def test(input0, output0, axes, keep_dims, input_data, output_data): argument
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| D | reduce_min.mod.py | 17 def test(input0, output0, axes, keep_dims, input_data, output_data): argument
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| /packages/modules/NeuralNetworks/runtime/test/specs/V1_3/ |
| D | unidirectional_sequence_rnn.mod.py | 21 recurrent_weights_data, bias_data, hidden_state_data, output_data, argument
116 output_data = [ variable
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| D | abs_int32.mod.py | 22 output_data = [abs(x) for x in input_data] variable
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| D | fill.mod.py | 16 def test(name, input_dims, value, output, input_dims_data, output_data): argument
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| D | pow_same_shape.mod.py | 22 output_data = [base_data[i]**exponent_data[i] for i in range(len(base_data))] variable
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| D | reduce_min_quant8_signed.mod.py | 17 def test(input0, output0, axes, keep_dims, input_data, output_data): argument
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| D | reduce_max_quant8_signed.mod.py | 17 def test(input0, output0, axes, keep_dims, input_data, output_data): argument
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| D | equal_quant8_signed.mod.py | 16 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
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| D | greater_equal_quant8_signed.mod.py | 16 def test(name, input0, input1, output0, input0_data, input1_data, output_data): argument
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| /packages/modules/NeuralNetworks/runtime/test/specs/AIDL_V2/ |
| D | pack.mod.py | 16 def test(name, axis_value, input_tensors, output_tensor, inputs_data, output_data): argument
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