| /frameworks/ml/nn/runtime/test/specs/V1_2/ |
| D | gather.mod.py | 17 def test(input0, axis, indices, output0, input_data, output_data): argument
36 input0: input_data,
45 input_data=[-2.0, 0.2,
56 input_data=[-2.0, 0.2,
66 input_data=[1, 2, 3],
75 input_data=[1, 2, 3],
84 input_data=[-2.0, 0.2,
97 input_data=[-2.0, 0.2, 0.7, 0.8],
106 input_data=[1, 2, 3,
117 input_data=[1, 2, 3,
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| D | log_softmax.mod.py | 19 def test(input0, output0, input_data, beta, axis, output_data): argument
22 input0: input_data,
29 input_data=[0, -6, 2, 4,
40 input_data=[0, -6,
55 input_data=[0, 2, 3, 10,
66 input_data=[0, -.6, .2, .4,
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| D | reduce_prod.mod.py | 17 def test(input0, output0, axes, keep_dims, input_data, output_data): argument
20 input0: input_data,
26 input_data=[-1, -2,
39 input_data=[9.527],
48 input_data=[1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0,
59 input_data=[1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0,
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| D | reduce_sum.mod.py | 17 def test(input0, output0, axes, keep_dims, input_data, output_data): argument
20 input0: input_data,
26 input_data=[-1, -2,
39 input_data=[9.527],
48 input_data=[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8,
59 input_data=[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8,
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| D | reduce_max.mod.py | 17 def test(input0, output0, axes, keep_dims, input_data, output_data): argument
24 input0: input_data,
30 input_data=[-1, -2,
43 input_data=[9.527],
52 input_data=[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8,
63 input_data=[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8,
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| D | reduce_min.mod.py | 17 def test(input0, output0, axes, keep_dims, input_data, output_data): argument
24 input0: input_data,
30 input_data=[-1, -2,
43 input_data=[9.527],
52 input_data=[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8,
63 input_data=[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8,
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| D | unidirectional_sequence_rnn.mod.py | 20 activation, time_major, output, input_data, weights_data, argument
28 input: input_data,
49 input_data = [ variable
154 input_data=input_data,
176 input_data=convert_to_time_major(input_data, num_batches, max_time,
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| D | reduce_all.mod.py | 17 def test(input0, output0, axes, keep_dims, input_data, output_data): argument
20 input0: input_data,
26 input_data=[False],
35 input_data=[True, True, True, True, True, False,
45 input_data=[True, True, True, True, True, True,
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| D | reduce_any.mod.py | 17 def test(input0, output0, axes, keep_dims, input_data, output_data): argument
20 input0: input_data,
28 input_data=[False],
37 input_data=[False, False, False, False, False, False,
47 input_data=[False, False, False, False, False, False,
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| D | bidirectional_sequence_rnn.mod.py | 41 time_major, merge_outputs, fw_output, bw_output, input_data, argument
61 input: input_data,
88 input_data = [ variable
241 input_data=input_data,
291 input_data=convert_to_time_major(input_data,
342 input_data=convert_to_time_major(input_data,
398 input_data=reverse_batch_major(input_data, [num_batches, max_time, input_size]),
452 input_data=[0] * num_batches * max_time * input_size,
461 aux_input_data=input_data,
471 input_data, [num_batches, max_time, input_size])
[all …]
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| D | neg.mod.py | 21 input_data = [(i - 60) / 10 for i in range(120)] variable
22 output_data = [-x for x in input_data]
25 input0: input_data,
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| D | abs.mod.py | 21 input_data = [(i - 60) / 10 for i in range(120)] variable
22 output_data = [abs(x) for x in input_data]
25 input0: input_data,
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| D | sqrt.mod.py | 23 input_data = [i / 10 for i in range(120)] variable
24 output_data = [math.sqrt(x) for x in input_data]
27 input0: input_data,
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| D | log.mod.py | 23 input_data = [(i + 1) / 10 for i in range(120)] variable
24 output_data = [math.log(x) for x in input_data]
27 input0: input_data,
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| /frameworks/ml/nn/runtime/test/specs/V1_3/ |
| D | gather_quant8_signed.mod.py | 46 def test(input0, axis, indices, output0, input_data, output_data): argument
55 input0: input_data,
64 input_data=[-2.0, 0.2,
75 input_data=[-2.0, 0.2,
85 input_data=[1, 2, 3],
94 input_data=[1, 2, 3],
103 input_data=[-2.0, 0.2,
116 input_data=[-2.0, 0.2, 0.7, 0.8],
125 input_data=[1, 2, 3,
136 input_data=[1, 2, 3,
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| D | reduce_max_quant8_signed.mod.py | 17 def test(input0, output0, axes, keep_dims, input_data, output_data): argument
24 input0: input_data,
30 input_data=[-1, -2,
43 input_data=[9.527],
52 input_data=[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8,
63 input_data=[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8,
|
| D | reduce_min_quant8_signed.mod.py | 17 def test(input0, output0, axes, keep_dims, input_data, output_data): argument
24 input0: input_data,
30 input_data=[-1, -2,
43 input_data=[9.527],
52 input_data=[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8,
63 input_data=[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8,
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| D | unidirectional_sequence_rnn.mod.py | 20 activation, time_major, output, output_state, input_data, weights_data, argument
30 input: input_data,
52 input_data = [ variable
194 input_data=input_data,
220 input_data=convert_to_time_major(input_data, num_batches, max_time,
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| D | if_simple.mod.py | 19 input_data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12] variable
20 output_add = [y + 10 for y in input_data]
21 output_sub = [y - 10 for y in input_data]
46 Test(x_data=True, y_data=input_data, z_data=output_add, name="true")
47 Test(x_data=False, y_data=input_data, z_data=output_sub, name="false")
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| D | bidirectional_sequence_rnn_1_3.mod.py | 41 time_major, merge_outputs, fw_output, bw_output, input_data, argument
67 input: input_data,
94 input_data = [ variable
247 input_data=[0] * len(input_data),
256 aux_input_data=input_data,
297 input_data=[0] * len(input_data),
306 aux_input_data=convert_to_time_major(input_data,
349 input_data=convert_to_time_major(input_data,
359 aux_input_data=convert_to_time_major(input_data,
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| D | if_same_branch_model.mod.py | 20 input_data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12] variable
21 output_add = [y + 10 for y in input_data]
47 Test(x=True, y=input_data, z=output_add, name="true")
48 Test(x=False, y=input_data, z=output_add, name="false")
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| D | bidirectional_sequence_rnn_state_output.mod.py | 46 input_data, fw_weights_data, fw_recurrent_weights_data, fw_bias_data, argument
67 input: input_data,
96 input_data = [ variable
256 input_data=input_data,
312 input_data=convert_to_time_major(input_data,
370 input_data=convert_to_time_major(input_data,
434 input_data=reverse_batch_major(input_data,
499 input_data=[0] * num_batches * max_time * input_size,
508 aux_input_data=input_data,
520 input_data, [num_batches, max_time, input_size])
[all …]
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| D | abs_int32.mod.py | 21 input_data = [i - 60 for i in range(119)] + [-(2 ** 24 + 1)] variable
22 output_data = [abs(x) for x in input_data]
25 input0: input_data,
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| /frameworks/ml/nn/runtime/test/specs/V1_3_cts_only/ |
| D | if_simple_unknown_dimension.mod.py | 19 input_data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12] variable
20 output_add = [y + 10 for y in input_data]
21 output_sub = [y - 10 for y in input_data]
47 Test(x_data=True, y_data=input_data, z_data=output_add, name="true")
48 Test(x_data=False, y_data=input_data, z_data=output_sub, name="false")
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| D | if_simple_unknown_rank.mod.py | 19 input_data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12] variable
20 output_add = [y + 10 for y in input_data]
21 output_sub = [y - 10 for y in input_data]
47 Test(x_data=True, y_data=input_data, z_data=output_add, name="true")
48 Test(x_data=False, y_data=input_data, z_data=output_sub, name="false")
|