| /frameworks/ml/nn/runtime/test/specs/V1_0/ |
| concat_quant8_3.mod.py | 28 output = Output("output", "TENSOR_QUANT8_ASYMM", "{%d, %d}, 0.5f, 0" % (row, output_col)) variable
29 model = model.Operation("CONCATENATION", input1, input2, axis1).To(output)
44 output0 = {output: output_values}
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| conv_quant8_2.mod.py | 26 output = Output("op4", "TENSOR_QUANT8_ASYMM", "{1, 2, 2, 1}, 1.f, 127") variable
29 stride1, act_none).To(output)
40 output: # output 0
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| depthwise_conv2d_float.mod.py | 25 output = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 4}") variable
31 cm, act).To(output)
44 output0 = {output: # output 0
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| depthwise_conv2d_float_2.mod.py | 25 output = Output("op4", "TENSOR_FLOAT32", "{1, 2, 1, 4}") variable
31 cm, act_none).To(output)
39 output0 = {output: # output 0
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| depthwise_conv2d_float_large.mod.py | 25 output = Output("op4", "TENSOR_FLOAT32", "{1, 1, 1, 2}") variable
31 cm, act).To(output)
40 output0 = {output: # output 0
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| depthwise_conv2d_float_large_2.mod.py | 25 output = Output("op4", "TENSOR_FLOAT32", "{1, 1, 1, 4}") variable
31 cm, act).To(output)
42 output0 = {output: # output 0
|
| depthwise_conv2d_float_large_2_weights_as_inputs.mod.py | 25 output = Output("op4", "TENSOR_FLOAT32", "{1, 1, 1, 4}") variable
31 cm, act).To(output)
49 output0 = {output: # output 0
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| depthwise_conv2d_float_large_weights_as_inputs.mod.py | 25 output = Output("op4", "TENSOR_FLOAT32", "{1, 1, 1, 2}") variable
31 cm, act).To(output)
45 output0 = {output: # output 0
|
| depthwise_conv2d_float_weights_as_inputs.mod.py | 25 output = Output("op4", "TENSOR_FLOAT32", "{1, 2, 2, 4}") variable
31 cm, act).To(output)
51 output0 = {output: # output 0
|
| depthwise_conv2d_quant8.mod.py | 25 output = Output("op4", "TENSOR_QUANT8_ASYMM", "{1,1,1,2}, 1.f, 0") variable
31 cm, act).To(output)
37 output0 = {output: # output 0
|
| depthwise_conv2d_quant8_2.mod.py | 25 output = Output("op4", "TENSOR_QUANT8_ASYMM", "{1, 2, 1, 4}, 1.f, 127") variable
31 cm, act_none).To(output)
39 output0 = {output: # output 0
|
| depthwise_conv2d_quant8_large.mod.py | 25 output = Output("op4", "TENSOR_QUANT8_ASYMM", "{1, 1, 1, 2}, 1.f, 0") variable
31 cm, act).To(output)
37 output0 = {output: # output 0
|
| depthwise_conv2d_quant8_large_weights_as_inputs.mod.py | 25 output = Output("op4", "TENSOR_QUANT8_ASYMM", "{1, 1, 1, 2}, 1.f, 0") variable
31 cm, act).To(output)
41 output0 = {output: # output 0
|
| depthwise_conv2d_quant8_weights_as_inputs.mod.py | 25 output = Output("op4", "TENSOR_QUANT8_ASYMM", "{1,1,1,2}, 1.f, 0") variable
31 cm, act).To(output)
41 output0 = {output: # output 0
|
| embedding_lookup.mod.py | 31 output = Output("output", "TENSOR_FLOAT32", "{%d, %d, %d}" % (lookups, columns, features)) variable
32 model = model.Operation("EMBEDDING_LOOKUP", index, value).To(output)
37 output0 = {output:
|
| hashtable_lookup_float.mod.py | 32 output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (lookups, features)) variable
33 hits = Output("hits", "TENSOR_QUANT8_ASYMM", "{%d}, 1.f, 0" % (lookups))
34 model = model.Operation("HASHTABLE_LOOKUP", lookup, key, value).To([output, hits])
40 output0 = {output:
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| hashtable_lookup_quant8.mod.py | 32 output = Output("output", "TENSOR_QUANT8_ASYMM", "{%d, %d}, 0.5f, 0" % (lookups, features)) variable
33 hits = Output("hits", "TENSOR_QUANT8_ASYMM", "{%d}, 1.f, 0" % (lookups))
34 model = model.Operation("HASHTABLE_LOOKUP", lookup, key, value).To([output, hits])
40 output0 = {output:
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| logistic_float_2.mod.py | 27 output = Output("output", "TENSOR_FLOAT32", "{%d, %d, %d, %d}" % (d0, d1, d2, d3)) variable
29 model = model.Operation("LOGISTIC", i0).To(output)
36 output0 = {output: output_values}
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| logistic_quant8_2.mod.py | 27 output = Output("output", "TENSOR_QUANT8_ASYMM", "{%d, %d, %d, %d}, 0.00390625f, 0" % (d0, d1, d2, d3)) variable
29 model = model.Operation("LOGISTIC", i0).To(output)
39 output0 = {output: output_values}
|
| lsh_projection.mod.py | 28 output = Output("output", "TENSOR_INT32", "{%d}" % (num_hash * num_bits)) variable
30 type_param).To(output)
37 output0 = {output: [1, 1, 1, 0, 1, 1, 1, 0]}
|
| lsh_projection_2.mod.py | 28 output = Output("output", "TENSOR_INT32", "{%d}" % (num_hash)) variable
30 type_param).To(output)
39 output0 = {output: [1, 2, 2, 0]}
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| lsh_projection_weights_as_inputs.mod.py | 27 output = Output("output", "TENSOR_INT32", "{%d}" % (num_hash * num_bits)) variable
28 model = model.Operation("LSH_PROJECTION", hhash, lookup, weight, type_param).To(output)
35 output0 = {output: [1, 1, 1, 0, 1, 1, 1, 0]}
|
| relu1_float_2.mod.py | 27 output = Output("output", "TENSOR_FLOAT32", "{%d, %d, %d, %d}" % (d0, d1, d2, d3)) variable
29 model = model.Operation("RELU1", i0).To(output)
36 output0 = {output: output_values}
|
| relu1_quant8_2.mod.py | 27 output = Output("output", "TENSOR_QUANT8_ASYMM", "{%d, %d, %d, %d}, 1.f, 128" % (d0, d1, d2, d3)) variable
29 model = model.Operation("RELU1", i0).To(output)
36 output0 = {output: output_values}
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| relu6_float_2.mod.py | 27 output = Output("output", "TENSOR_FLOAT32", "{%d, %d, %d, %d}" % (d0, d1, d2, d3)) variable
29 model = model.Operation("RELU6", i0).To(output)
36 output0 = {output: output_values}
|
