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/packages/modules/NeuralNetworks/runtime/test/specs/V1_3/
Ddepthwise_conv2d_quant8_signed.mod.py21 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [.25, 0., .2, 0., .25, 0., 0., .3, .25, 0.,… variable
24 Model().Operation("DEPTHWISE_CONV_2D", i1, f1, b1, 0, 0, 0, 0, 1, 1, 2, 0, layout, 1, 1).To(o1)
29 f1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.01, -128),
78 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [.25, 0., .2, 0., .25, 0., 0., .3, .25, 0.,… variable
81 Model().Operation("DEPTHWISE_CONV_2D", i1, f1, b1, 2, 1, 1, 2, 0, layout, 1, 1).To(o1)
86 f1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.01, -128),
165 f1 = Parameter("op2", "TENSOR_QUANT8_SYMM_PER_CHANNEL", "{1, 2, 2, 2}", variable
170 Model("same").Operation("DEPTHWISE_CONV_2D", i1, f1, b1, 0, 0, 0, 0, 1, 1, 1, 0).To(o1)
220 f1 = Parameter("op2", "TENSOR_QUANT8_ASYMM_SIGNED", "{1, 2, 2, 4}, 0.5f, -1", [1, 3, 5, 7, -19, 19,… variable
229 i1, f1, b1,
[all …]
Dconv2d_quant8_signed.mod.py21 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [.25, .25, .25, .25]) variable
24 Model().Operation("CONV_2D", i1, f1, b1, 0, 0, 0, 0, 1, 1, 0, layout, 1, 1).To(o1)
29 f1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.125, -128),
72 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [.25, .25, .25, .25]) variable
75 Model().Operation("CONV_2D", i1, f1, b1, 2, 1, 1, 0, layout, 1, 1).To(o1)
80 f1: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.125, -128),
150 f1 = Parameter("op2", "TENSOR_QUANT8_SYMM_PER_CHANNEL", "{3, 1, 1, 2}", variable
154 Model().Operation("CONV_2D", i1, f1, b1, 0, 0, 0, 0, 1, 1, 0).To(o1)
211 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [.25, .25, .25, .25]) variable
214 Model().Operation("CONV_2D", i1, f1, b1, 0, 0, 0, 0, 1, 1, 0, layout).To(o1)
[all …]
/packages/modules/NeuralNetworks/tools/test_generator/tests/P_implicit_variation/
Dconv_float.mod.py17 f1 = Parameter("op2", "TENSOR_FLOAT32", "{2, 2, 2, 2}", [1, 2, 3, 4, 5, 6, 7, 8, 8, 7, 6, 5, 4, 3, … variable
23 model = model.Operation("CONV_2D", i1, f1, b1, 1, 1, 1, act, layout).To(output)
34 f1: ("TENSOR_QUANT8_ASYMM", 0.25, 128),
43 ("NCHW", [i1, f1, output], [layout])
49 ("as_input", [f1])
/packages/modules/NeuralNetworks/tools/test_generator/tests/P_vts_implicit_variation/
Dconv_float.mod.py17 f1 = Parameter("op2", "TENSOR_FLOAT32", "{2, 2, 2, 2}", [1, 2, 3, 4, 5, 6, 7, 8, 8, 7, 6, 5, 4, 3, … variable
23 model = model.Operation("CONV_2D", i1, f1, b1, 1, 1, 1, act, layout).To(output)
34 f1: ("TENSOR_QUANT8_ASYMM", 0.25, 128),
43 ("NCHW", [i1, f1, output], [layout])
49 ("as_input", [f1])
/packages/modules/NeuralNetworks/tools/test_generator/tests/P_variation/
Dconv_float.mod.py17 f1 = Parameter("op2", "TENSOR_FLOAT32", "{2, 2, 2, 2}", [1, 2, 3, 4, 5, 6, 7, 8, 8, 7, 6, 5, 4, 3, … variable
26 model = model.Operation("CONV_2D", i1, f1, b1, pad, stride0, stride1, act, layout).To(output)
37 f1: ("TENSOR_QUANT8_ASYMM", 0.25, 128),
43 Example((input0, output0)).AddNchw(i1, f1, output, layout).AddAllActivations(
44 output, act).AddInput(f1).AddVariations(RelaxedModeConverter(True), quant8)
/packages/modules/NeuralNetworks/tools/test_generator/tests/P_vts_variation/
Dconv_float.mod.py17 f1 = Parameter("op2", "TENSOR_FLOAT32", "{2, 2, 2, 2}", [1, 2, 3, 4, 5, 6, 7, 8, 8, 7, 6, 5, 4, 3, … variable
26 model = model.Operation("CONV_2D", i1, f1, b1, pad, stride0, stride1, act, layout).To(output)
37 f1: ("TENSOR_QUANT8_ASYMM", 0.25, 128),
45 Example((input0, output0)).AddNchw(i1, f1, output, layout).AddAllActivations(
46 output, act).AddInput(f1).AddVariations(RelaxedModeConverter(True), quant8)
/packages/modules/NeuralNetworks/runtime/test/specs/V1_2/
Ddepthwise_conv2d_dilation.mod.py21 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [.25, 0., .2, 0., .25, 0., 0., .3, .25, 0.,… variable
24 Model().Operation("DEPTHWISE_CONV_2D", i1, f1, b1, 0, 0, 0, 0, 1, 1, 2, 0, layout, 1, 1).To(o1)
29 f1: ("TENSOR_QUANT8_ASYMM", 0.01, 0),
76 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [.25, 0., .2, 0., .25, 0., 0., .3, .25, 0.,… variable
79 Model().Operation("DEPTHWISE_CONV_2D", i1, f1, b1, 2, 1, 1, 2, 0, layout, 1, 1).To(o1)
84 f1: ("TENSOR_QUANT8_ASYMM", 0.01, 0),
Dconv2d_dilation.mod.py21 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [.25, .25, .25, .25]) variable
24 Model().Operation("CONV_2D", i1, f1, b1, 0, 0, 0, 0, 1, 1, 0, layout, 1, 1).To(o1)
29 f1: ("TENSOR_QUANT8_ASYMM", 0.125, 0),
72 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 1}", [.25, .25, .25, .25]) variable
75 Model().Operation("CONV_2D", i1, f1, b1, 2, 1, 1, 0, layout, 1, 1).To(o1)
80 f1: ("TENSOR_QUANT8_ASYMM", 0.125, 0),
Ddepthwise_conv2d_invalid_filter_dims.mod.py23 f1 = Parameter("op2", "TENSOR_FLOAT32", "{2, 2, 2, 4}", [0.] * (2 * 2 * 2 * 4)) variable
26 Model().Operation("DEPTHWISE_CONV_2D", i1, f1, b1, 0, 0, 0, 0, 1, 1, 2, 0, layout).To(o1)
31 f1: ("TENSOR_QUANT8_ASYMM", 0.01, 0),
37 f1: ("TENSOR_QUANT8_SYMM_PER_CHANNEL", 0, 0,
Ddepthwise_conv2d_v1_2.mod.py21 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [.25, 0., .2, 0., .25, 0., 0., .3, .25, 0.,… variable
24 Model().Operation("DEPTHWISE_CONV_2D", i1, f1, b1, 0, 0, 0, 0, 1, 1, 2, 0, layout).To(o1)
29 f1: ("TENSOR_QUANT8_ASYMM", 0.01, 0),
35 …f1: ("TENSOR_QUANT8_SYMM_PER_CHANNEL", 0, 0, SymmPerChannelQuantParams(channelDim=3, scales=[0.01,…
41 …f1: ("TENSOR_QUANT8_SYMM_PER_CHANNEL", 0, 0, SymmPerChannelQuantParams(channelDim=3, scales=[0.01,…
/packages/modules/NeuralNetworks/tools/test_generator/tests/P_naming/
Dconv_float.mod.py17 f1 = Parameter("op2", "TENSOR_FLOAT32", "{2, 2, 2, 2}", [1, 2, 3, 4, 5, 6, 7, 8, 8, 7, 6, 5, 4, 3, … variable
26 model = model.Operation("CONV_2D", i1, f1, b1, pad, stride0, stride1, act, layout).To(output)
37 f1: ("TENSOR_QUANT8_ASYMM", 0.25, 128),
41 nchw = DataLayoutConverter("NCHW", name="nchw_layout").Identify([i1, f1, output], [layout])
44 weight_as_input = ParameterAsInputConverter(name="w_as_input").Identify([f1])
/packages/modules/NeuralNetworks/tools/test_generator/tests/P_vts_naming/
Dconv_float.mod.py17 f1 = Parameter("op2", "TENSOR_FLOAT32", "{2, 2, 2, 2}", [1, 2, 3, 4, 5, 6, 7, 8, 8, 7, 6, 5, 4, 3, … variable
26 model = model.Operation("CONV_2D", i1, f1, b1, pad, stride0, stride1, act, layout).To(output)
37 f1: ("TENSOR_QUANT8_ASYMM", 0.25, 128),
41 nchw = DataLayoutConverter("NCHW", name="nchw_layout").Identify([i1, f1, output], [layout])
44 weight_as_input = ParameterAsInputConverter(name="w_as_input").Identify([f1])
/packages/apps/Camera2/src/com/android/camera/async/
DFutures2.java88 final ListenableFuture<T1> f1,
93 futures[0] = f1;
118 final ListenableFuture<T1> f1,
121 return joinAll(f1, f2, new ImmediateAsyncFunction2<>(fn));
131 final ListenableFuture<T1> f1,
137 futures[0] = f1;
164 final ListenableFuture<T1> f1,
168 return joinAll(f1, f2, f3, new ImmediateAsyncFunction3<>(fn));
/packages/modules/NeuralNetworks/runtime/test/specs/V1_3_cts_only/
Dconv2d_v1_3_invalid_rank.mod.py21 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2}", [.25, .25, .25, .25]) variable
24 Model().Operation("CONV_2D", i1, f1, b1, 0, 0, 0, 0, 1, 1, 0, layout).To(o1)
29 f1: ("TENSOR_QUANT8_ASYMM", 0.125, 0),
35 f1: ("TENSOR_QUANT8_SYMM_PER_CHANNEL", 0, 0,
/packages/modules/NeuralNetworks/runtime/test/specs/V1_0/
Dconv_float_weights_as_inputs.mod.py19 f1 = Input("op2", "TENSOR_FLOAT32", "{1, 2, 2, 1}") variable
28 model = model.Operation("CONV_2D", i1, f1, b1, pad0, pad0, pad0, pad0, stride, stride, act).To(outp…
33 f1:
Dconv_quant8_large_weights_as_inputs.mod.py19 f1 = Input("op2", "TENSOR_QUANT8_ASYMM", "{3, 1, 1, 3}, 0.5, 0") variable
26 model = model.Operation("CONV_2D", i1, f1, b1, pad0, pad0, pad0, pad0, stride, stride, act).To(outp…
32 f1:
Dconv_quant8_channels_weights_as_inputs.mod.py19 f1 = Input("op2", "TENSOR_QUANT8_ASYMM", "{3, 1, 1, 3}, 0.5f, 0") variable
26 model = model.Operation("CONV_2D", i1, f1, b1, pad0, pad0, pad0, pad0, stride, stride, act).To(outp…
31 f1:
Dconv_quant8_overflow_weights_as_inputs.mod.py19 f1 = Input("op2", "TENSOR_QUANT8_ASYMM", "{3, 1, 1, 3}, 0.5, 0") variable
26 model = model.Operation("CONV_2D", i1, f1, b1, pad0, pad0, pad0, pad0, stride, stride, act).To(outp…
32 f1:
Dconv_float_large_weights_as_inputs.mod.py19 f1 = Input("op2", "TENSOR_FLOAT32", "{3, 1, 1, 3}") variable
28 model = model.Operation("CONV_2D", i1, f1, b1, pad0, pad0, pad0, pad0, stride, stride, act).To(outp…
34 f1:
Dconv_quant8_weights_as_inputs.mod.py19 f1 = Input("op2", "TENSOR_QUANT8_ASYMM", "{1, 2, 2, 1}, 0.5f, 0") variable
28 model = model.Operation("CONV_2D", i1, f1, b1, pad0, pad0, pad0, pad0, stride, stride, act).To(outp…
33 f1:
Dconv_float_channels_weights_as_inputs.mod.py19 f1 = Input("op2", "TENSOR_FLOAT32", "{3, 1, 1, 3}") variable
28 model = model.Operation("CONV_2D", i1, f1, b1, pad0, pad0, pad0, pad0, stride, stride, act).To(outp…
33 f1:
Ddepthwise_conv2d_quant8_weights_as_inputs.mod.py19 f1 = Input("op2", "TENSOR_QUANT8_ASYMM", "{1, 2, 2, 2}, 0.5f, 0") variable
28 i1, f1, b1,
36 f1:
Ddepthwise_conv2d_quant8_large_weights_as_inputs.mod.py19 f1 = Input("op2", "TENSOR_QUANT8_ASYMM", "{1, 2, 2, 2}, 0.5f, 0") variable
28 i1, f1, b1,
36 f1:
Ddepthwise_conv2d_float_large_weights_as_inputs.mod.py19 f1 = Input("op2", "TENSOR_FLOAT32", "{1, 2, 2, 2}") # depth_out = 2 variable
28 i1, f1, b1,
38 f1: [
/packages/modules/NeuralNetworks/tools/test_generator/tests/P_backward_compatibility_quant8/
Ddepthwise_conv2d_quant8.mod.py17 f1 = Input("op2", "TENSOR_QUANT8_ASYMM", "{1, 2, 2, 2}, 0.5f, 0") variable
26 i1, f1, b1,
34 f1:

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