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/packages/modules/NeuralNetworks/runtime/test/specs/V1_3/
Droi_align_quant8_signed.mod.py175 i4 = Input("in", "TENSOR_FLOAT32", "{4, 4, 4, 1}") variable
178 Model().Operation("ROI_ALIGN", i4, roi4, [2, 2, 2, 2, 2], 2, 2, 2.0, 1.0, 0, 4, layout).To(o4)
181 i4: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.25, 0),
188 i4: [
211 }).AddNchw(i4, o4, layout).AddVariations(quant8_signed, includeDefault=False)
248 i4 = Input("in", "TENSOR_FLOAT32", "{1, 512, 8, 1}") variable
251 Model().Operation("ROI_ALIGN", i4, roi4, [0], 128, 4, 1.0, 64.0, 10, 10, layout).To(o4)
254 i4: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.25, 0),
261 i4: [0] * (512 * 8),
264 }).AddNchw(i4, o4, layout).AddVariations(quant8_signed, includeDefault=False)
Dgenerate_proposals_quant8_signed.mod.py23 i4 = Input("imageInfo", "TENSOR_FLOAT32", "{1, 2}") # image info variable
28 i1, i2, i3, i4, 4.0, 4.0, -1, -1, 0.30, 1.0, layout).To(o1, o2, o3)
34 i4: ("TENSOR_QUANT16_ASYMM", 0.125, 0),
51 i4: [32, 32], # image info
73 i4 = Input("imageInfo", "TENSOR_FLOAT32", "{2, 2}") # image info variable
78 i1, i2, i3, i4, 10.0, 10.0, 32, 16, 0.20, 1.0, layout).To(o1, o2, o3)
84 i4: ("TENSOR_QUANT16_ASYMM", 0.125, 0),
164 i4: [64, 64, 32, 32], # image info
Dspace_to_batch_quant8_signed.mod.py195 i4 = Input("op1", "TENSOR_FLOAT32", "{1, 4, 2, 1}") variable
198 Model().Operation("SPACE_TO_BATCH_ND", i4, [3, 2], pad4, layout).To(o4)
202 i4: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.25, 0),
208 i4: [1, 2, 3, 4, 5, 6, 7, 8],
212 }).AddNchw(i4, o4, layout).AddVariations(quant8_signed, includeDefault=False)
Dtranspose_conv2d_quant8_signed.mod.py162 i4 = Input("op1", "TENSOR_FLOAT32", "{1, 4, 4, 2}") # input 0 variable
167 Model().Operation("TRANSPOSE_CONV_2D", i4, w4, b4, s4, 2, 1, 1, 0, layout).To(o4)
171 i4: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.25, -118),
178 i4: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,
186 }).AddNchw(i4, o4, s4, layout).AddVariations(quant8_signed, includeDefault=False)
Ddepthwise_conv2d_quant8_signed.mod.py472 i4 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 4}") variable
476 Model("large").Operation("DEPTHWISE_CONV_2D", i4, f4, b4, 0, 0, 0, 0, 1, 1, 1, 0, layout).To(o4)
480 i4: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, 0),
486 i4: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.5, 0),
494 i4: [10, 21, 10, 0,
499 }).AddNchw(i4, o4, layout).AddVariations(quant8_signed, includeDefault=False)
Dtranspose_quant8_signed.mod.py163 i4 = Input("op1", "TENSOR_FLOAT32", "{1, 4, 4, 2}") # input 0 variable
168 Model().Operation("TRANSPOSE_CONV_2D", i4, w4, b4, s4, 2, 1, 1, 0, layout).To(o4)
172 i4: ("TENSOR_QUANT8_ASYMM_SIGNED", 0.25, -118),
179 i4: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,
187 }).AddNchw(i4, o4, s4, layout).AddVariations(quant8_signed, includeDefault=False)
/packages/modules/NeuralNetworks/runtime/test/specs/V1_2/
Droi_align.mod.py175 i4 = Input("in", "TENSOR_FLOAT32", "{4, 4, 4, 1}") variable
178 Model().Operation("ROI_ALIGN", i4, roi4, [2, 2, 2, 2, 2], 2, 2, 2.0, 1.0, 0, 4, layout).To(o4)
181 i4: ("TENSOR_QUANT8_ASYMM", 0.25, 128),
188 i4: [
211 }).AddNchw(i4, o4, layout).AddVariations("relaxed", quant8, "float16")
248 i4 = Input("in", "TENSOR_FLOAT32", "{1, 512, 8, 1}") variable
251 Model().Operation("ROI_ALIGN", i4, roi4, [0], 128, 4, 1.0, 64.0, 10, 10, layout).To(o4)
254 i4: ("TENSOR_QUANT8_ASYMM", 0.25, 128),
261 i4: [0] * (512 * 8),
264 }).AddNchw(i4, o4, layout).AddVariations("relaxed", quant8, "float16")
Dgenerate_proposals.mod.py24 i4 = Input("imageInfo", "TENSOR_FLOAT32", "{1, 2}") # image info variable
29 i1, i2, i3, i4, 4.0, 4.0, -1, -1, 0.30, 1.0, layout).To(o1, o2, o3)
35 i4: ("TENSOR_QUANT16_ASYMM", 0.125, 0),
52 i4: [32, 32], # image info
73 i4 = Input("imageInfo", "TENSOR_FLOAT32", "{2, 2}") # image info variable
78 i1, i2, i3, i4, 10.0, 10.0, 32, 16, 0.20, 1.0, layout).To(o1, o2, o3)
84 i4: ("TENSOR_QUANT16_ASYMM", 0.125, 0),
164 i4: [64, 64, 32, 32], # image info
Dspace_to_batch_v1_2.mod.py77 i4 = Input("op1", "TENSOR_FLOAT32", "{1, 4, 2, 1}") variable
80 Model().Operation("SPACE_TO_BATCH_ND", i4, [3, 2], pad4, layout).To(o4)
84 i4: ("TENSOR_QUANT8_ASYMM", 0.25, 128),
90 i4: [1, 2, 3, 4, 5, 6, 7, 8],
94 }).AddNchw(i4, o4, layout).AddVariations("relaxed", "float16", quant8)
Ddepthwise_conv2d_v1_2.mod.py115 i4 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 4}") variable
119 Model("large").Operation("DEPTHWISE_CONV_2D", i4, f4, b4, 0, 0, 0, 0, 1, 1, 1, 0, layout).To(o4)
123 i4: ("TENSOR_QUANT8_ASYMM", 0.5, 128),
129 i4: ("TENSOR_QUANT8_ASYMM", 0.5, 128),
137 i4: [10, 21, 10, 0,
142 }).AddNchw(i4, o4, layout).AddVariations("relaxed", "float16", quant8, channelQuant8)
Dconv2d_v1_2.mod.py104 i4 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 3, 3}") variable
108 Model("large").Operation("CONV_2D", i4, f4, b4, 0, 0, 0, 0, 1, 1, 0, layout).To(o4)
112 i4: ("TENSOR_QUANT8_ASYMM", 0.5, 128),
118 i4: ("TENSOR_QUANT8_ASYMM", 0.5, 128),
124 i4: ("TENSOR_QUANT8_ASYMM", 1.0, 127),
132 i4: [1., 2., 3., 4., 5., 6., 7., 8., 9.,
140 }).AddNchw(i4, o4, layout).AddVariations("relaxed", quant8, channelQuant8, channelQuant8_mult_gt_1,…
Dmax_pool_v1_2.mod.py94 i4 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 4, 1}") variable
96 Model().Operation("MAX_POOL_2D", i4, 1, 2, 2, 2, 2, 0, layout).To(o4)
100 i4: ("TENSOR_QUANT8_ASYMM", 0.25, 0),
106 i4: [0, 6, 2, 4, 3, 2, 10, 7],
108 }).AddNchw(i4, o4, layout).AddVariations("relaxed", quant8, "float16")
Davg_pool_v1_2.mod.py106 i4 = Input("op1", ("TENSOR_FLOAT32", [bat, row, col, chn])) variable
108 Model().Operation("AVERAGE_POOL_2D", i4, pad, pad, pad, pad, std, std, flt, flt, 3, layout).To(o4)
112 i4: ("TENSOR_QUANT8_ASYMM", 0.5, 0),
118 i4: [10 for _ in range(bat * row * col * chn)],
120 }).AddNchw(i4, o4, layout).AddVariations("relaxed", "float16", quant8)
Dtranspose_conv2d.mod.py127 i4 = Input("op1", "TENSOR_FLOAT32", "{1, 4, 4, 2}") # input 0 variable
132 Model().Operation("TRANSPOSE_CONV_2D", i4, w4, b4, s4, 2, 1, 1, 0, layout).To(o4)
136 i4: ("TENSOR_QUANT8_ASYMM", 0.25, 10),
143 i4: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,
151 }).AddNchw(i4, o4, s4, layout).AddVariations("relaxed", quant8, "float16")
/packages/modules/NeuralNetworks/tools/test_generator/tests/P_internal/
Dadd_internal.mod.py21 i4 = Input("i4", ("TENSOR_FLOAT32", [2])) # input 0 variable
50 model.Operation("ADD", i3, i4, act).To(t2)
58 i4: [0, 0],
/packages/modules/NeuralNetworks/tools/test_generator/tests/P_vts_internal/
Dadd_internal.mod.py21 i4 = Input("i4", ("TENSOR_FLOAT32", [2])) # input 0 variable
50 model.Operation("ADD", i3, i4, act).To(t2)
58 i4: [0, 0],
/packages/modules/NeuralNetworks/runtime/test/specs/V1_0/
Dconv_1_h3_w2_SAME.mod.py2 i4 = Int32Scalar("b4", 1) variable
10 model = model.Operation("CONV_2D", i2, i0, i1, i4, i5, i6, i7).To(i3)
Dconv_3_h3_w2_SAME.mod.py2 i4 = Int32Scalar("b4", 1) variable
10 model = model.Operation("CONV_2D", i2, i0, i1, i4, i5, i6, i7).To(i3)
Dconv_3_h3_w2_VALID.mod.py2 i4 = Int32Scalar("b4", 2) variable
10 model = model.Operation("CONV_2D", i2, i0, i1, i4, i5, i6, i7).To(i3)
Dconv_1_h3_w2_VALID.mod.py2 i4 = Int32Scalar("b4", 2) variable
10 model = model.Operation("CONV_2D", i2, i0, i1, i4, i5, i6, i7).To(i3)
Ddepthwise_conv.mod.py2 i4 = Int32Scalar("b4", 1) variable
11 model = model.Operation("DEPTHWISE_CONV_2D", i2, i0, i1, i4, i5, i6, i7, i8).To(i3)
/packages/modules/NeuralNetworks/runtime/test/specs/V1_1/
Dconv_1_h3_w2_SAME_relaxed.mod.py18 i4 = Int32Scalar("b4", 1) variable
26 model = model.Operation("CONV_2D", i2, i0, i1, i4, i5, i6, i7).To(i3)
Dconv_1_h3_w2_VALID_relaxed.mod.py18 i4 = Int32Scalar("b4", 2) variable
26 model = model.Operation("CONV_2D", i2, i0, i1, i4, i5, i6, i7).To(i3)
Dconv_3_h3_w2_SAME_relaxed.mod.py18 i4 = Int32Scalar("b4", 1) variable
26 model = model.Operation("CONV_2D", i2, i0, i1, i4, i5, i6, i7).To(i3)
Dconv_3_h3_w2_VALID_relaxed.mod.py18 i4 = Int32Scalar("b4", 2) variable
26 model = model.Operation("CONV_2D", i2, i0, i1, i4, i5, i6, i7).To(i3)

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