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/aosp_15_r20/external/pytorch/test/quantization/pt2e/
H A Dtest_xnnpack_quantizer.py52 … # input and output are using quantize_per_tensor and weight is using quantize_per_channel
53 torch.ops.quantized_decomposed.quantize_per_tensor.default: 2,
61 torch.ops.quantized_decomposed.quantize_per_tensor.default,
77 … # input and output are using quantize_per_tensor and weight is using quantize_per_channel
78 torch.ops.quantized_decomposed.quantize_per_tensor.default: 2,
87 torch.ops.quantized_decomposed.quantize_per_tensor.default,
102 … # input and output are using quantize_per_tensor and weight is using quantize_per_channel
103 torch.ops.quantized_decomposed.quantize_per_tensor.default: 4,
111 torch.ops.quantized_decomposed.quantize_per_tensor.default,
114 torch.ops.quantized_decomposed.quantize_per_tensor.default,
[all …]
H A Dtest_x86inductor_quantizer.py596 torch.ops.quantized_decomposed.quantize_per_tensor.default: 1,
603 torch.ops.quantized_decomposed.quantize_per_tensor.default,
664 torch.ops.quantized_decomposed.quantize_per_tensor.default: 3,
671 torch.ops.quantized_decomposed.quantize_per_tensor.default,
702 torch.ops.quantized_decomposed.quantize_per_tensor.default: 2,
714 torch.ops.quantized_decomposed.quantize_per_tensor.default: 2,
721 torch.ops.quantized_decomposed.quantize_per_tensor.default,
752 torch.ops.quantized_decomposed.quantize_per_tensor.default: 2,
759 torch.ops.quantized_decomposed.quantize_per_tensor.default,
762 torch.ops.quantized_decomposed.quantize_per_tensor.default,
[all …]
H A Dtest_quantize_pt2e.py113 torch.ops.quantized_decomposed.quantize_per_tensor.default: 2,
120 torch.ops.quantized_decomposed.quantize_per_tensor.default,
186 torch.ops.quantized_decomposed.quantize_per_tensor.default
280 torch.ops.quantized_decomposed.quantize_per_tensor.default
295 torch.ops.quantized_decomposed.quantize_per_tensor.default
384 torch.ops.quantized_decomposed.quantize_per_tensor.default
402 torch.ops.quantized_decomposed.quantize_per_tensor.default
484 torch.ops.quantized_decomposed.quantize_per_tensor.default
507 torch.ops.quantized_decomposed.quantize_per_tensor.default
564 == torch.ops.quantized_decomposed.quantize_per_tensor.default
[all …]
H A Dtest_metadata_porting.py48 torch.ops.quantized_decomposed.quantize_per_tensor.default,
50 torch.ops.quantized_decomposed.quantize_per_tensor.tensor,
189 torch.ops.quantized_decomposed.quantize_per_tensor.default: quantize_per_tensor_tags,
239 torch.ops.quantized_decomposed.quantize_per_tensor.default: quantize_per_tensor_tags,
308 torch.ops.quantized_decomposed.quantize_per_tensor.default: quantize_per_tensor_tags,
309 … torch.ops.quantized_decomposed.quantize_per_tensor.tensor: quantize_per_tensor_tensor_tags,
373 … torch.ops.quantized_decomposed.quantize_per_tensor.tensor: quantize_per_tensor_tensor_tags,
417 … torch.ops.quantized_decomposed.quantize_per_tensor.tensor: quantize_per_tensor_tensor_tags,
511 … torch.ops.quantized_decomposed.quantize_per_tensor.default: quantize_per_tensor_tensor_tags,
/aosp_15_r20/external/pytorch/test/quantization/core/
H A Dtest_quantized_op.py207 qX = torch.quantize_per_tensor(X, scale=scale, zero_point=zero_point,
230 qY_hat = torch.quantize_per_tensor(dqY_hat, scale=output_scale,
417 qX = torch.quantize_per_tensor(X, scale=scale, zero_point=zero_point,
424 qY = torch.quantize_per_tensor(dqY, scale=scale, zero_point=zero_point,
441 qX = torch.quantize_per_tensor(X, scale=scale, zero_point=zero_point,
448 … qY_hat = torch.quantize_per_tensor(dqY_hat, scale=output_scale, zero_point=output_zero_point,
467 qX = torch.quantize_per_tensor(X, scale=scale, zero_point=zero_point,
473 … qY_hat = torch.quantize_per_tensor(dqY_hat, scale=output_scale, zero_point=output_zero_point,
498 qX = torch.quantize_per_tensor(X, scale=scale, zero_point=zero_point,
504 qY = torch.quantize_per_tensor(dqY, scale=scale, zero_point=zero_point,
[all …]
H A Dtest_quantized_tensor.py145 x_q = torch.quantize_per_tensor(x, 0.1, 10, torch.quint4x2)
146 y_q = torch.quantize_per_tensor(x, 0.1, 10, torch.quint4x2)
159 qx = torch.quantize_per_tensor(x, scale=scale, zero_point=zero_point, dtype=dtype)
170 qx = torch.quantize_per_tensor(x, scale=scale, zero_point=zero_point, dtype=dtype)
176 qx = torch.quantize_per_tensor(x, scale=scale, zero_point=zero_point, dtype=dtype)
222 q_s = torch.quantize_per_tensor(mat2quant, scale, zero_pt, dtype)
233 qr = torch.quantize_per_tensor(r, scale, zero_point, dtype)
252 empty_qr = torch.quantize_per_tensor(empty_r, scale, zero_point, dtype)
269 qr = torch.quantize_per_tensor(r, scale, zero_point, dtype)
292 qr = torch.quantize_per_tensor(r, scale, zero_point, dtype)
[all …]
H A Dtest_quantized_module.py61 qx = torch.quantize_per_tensor(x, 1.0, 0, dtype=torch.qint32)
116 W_q = torch.quantize_per_tensor(W, 0.1, W_zp, torch.qint8)
119 X_q = torch.quantize_per_tensor(X, 0.2, 10, torch.quint8)
255 qr = torch.quantize_per_tensor(r, scale, zero_point, dtype)
316 Y_exp = torch.quantize_per_tensor(
910 qX = torch.quantize_per_tensor(X, scale=scale, zero_point=zero_point,
930 quant_ref = torch.quantize_per_tensor(y_ref, 1.0, 0, dtype=torch.quint8)
933 qx = torch.quantize_per_tensor(x, 1.0, 0, dtype=torch.quint8)
981 quant_ref = torch.quantize_per_tensor(y_ref, 1.0, 0, dtype=torch.quint8)
984 qx = torch.quantize_per_tensor(x, 1.0, 0, dtype=torch.quint8)
[all …]
/aosp_15_r20/external/pytorch/test/cpp/tensorexpr/
H A Dtest_quantization.cpp38 %q.1 : QInt8(2, 2) = aten::quantize_per_tensor(%x.1, %4, %3, %2) in TEST_F()
45 auto q = at::quantize_per_tensor(x, 0.1f, 13, at::kQInt8); in TEST_F()
68 %q.1 : QUInt8(2, 2) = aten::quantize_per_tensor(%x.1, %4, %3, %2) in TEST_F()
75 auto q = at::quantize_per_tensor(x, 0.1f, 122, at::kQUInt8); in TEST_F()
98 %q.1 : QUInt8(1, 2, 2) = aten::quantize_per_tensor(%x.1, %4, %3, %2) in TEST_F()
107 auto q = at::quantize_per_tensor(x, 0.1f, 122, at::kQUInt8); in TEST_F()
147 %q1 : QInt8(2, 2) = aten::quantize_per_tensor(%x1, %qs1, %qz1, %2) in TEST_F()
148 %q2 : QInt8(2, 2) = aten::quantize_per_tensor(%x2, %qs2, %qz2, %2) in TEST_F()
157 auto q1 = at::quantize_per_tensor(x1, 0.1f, 13, at::kQInt8); in TEST_F()
158 auto q2 = at::quantize_per_tensor(x2, 0.1f, 13, at::kQInt8); in TEST_F()
[all …]
/aosp_15_r20/external/pytorch/torch/csrc/jit/passes/quantization/
H A Dquantization_patterns.h86 value + "_quant = aten::quantize_per_tensor(" + value + "_tensor" + in getQuantizeForScalar()
117 %r_quant = aten::quantize_per_tensor(%r, %r_scale, %r_zero_point, %r_dtype) in getInputTensorQParamOpPattern()
187 %r_quant = aten::quantize_per_tensor(%r, %r_scale, %r_zero_point, %r_dtype) in getClampOpFusionInfo()
214 %r_quant = aten::quantize_per_tensor(%r, %r_scale, %r_zero_point, %r_dtype) in getFixedQParamOpFusionInfo()
221 %r_quant = aten::quantize_per_tensor(%r, %r_scale, %r_zero_point, %r_dtype) in getFixedQParamOpFusionInfo()
249 // %r_quant = aten::quantize_per_tensor(%r, %r_scale, %r_zero_point,
270 %r_quant = aten::quantize_per_tensor(%r, %r_scale, %r_zero_point, %r_dtype) in getObservedQParamOpFusionInfo()
293 %r_quant = aten::quantize_per_tensor(%r, %r_scale, %r_zero_point, %r_dtype) in quant_fusion_pattern_and_replacements()
304 %r_quant = aten::quantize_per_tensor(%r, %r_scale, %r_zero_point, %r_dtype) in quant_fusion_pattern_and_replacements()
315 %r_quant = aten::quantize_per_tensor(%r, %r_scale, %r_zero_point, %r_dtype) in quant_fusion_pattern_and_replacements()
[all …]
/aosp_15_r20/external/executorch/backends/cadence/aot/tests/
H A Dtest_fusion_ops_passes.py224 x = torch.ops.quantized_decomposed.quantize_per_tensor(
245 exir_ops.edge.quantized_decomposed.quantize_per_tensor.default: 0,
257 x = torch.ops.quantized_decomposed.quantize_per_tensor(
276 exir_ops.edge.quantized_decomposed.quantize_per_tensor.default: 1,
288 x = torch.ops.quantized_decomposed.quantize_per_tensor(
308 exir_ops.edge.quantized_decomposed.quantize_per_tensor.default: 0,
324 x = torch.ops.quantized_decomposed.quantize_per_tensor(
338 exir_ops.edge.quantized_decomposed.quantize_per_tensor.default: 0,
354 x = torch.ops.quantized_decomposed.quantize_per_tensor(
368 exir_ops.edge.quantized_decomposed.quantize_per_tensor.default: 0,
[all …]
H A Dtest_reorder_ops_passes.py65 x1 = exir_ops.edge.quantized_decomposed.quantize_per_tensor(
69 x2 = exir_ops.edge.quantized_decomposed.quantize_per_tensor(
73 x3 = exir_ops.edge.quantized_decomposed.quantize_per_tensor(
77 x4 = exir_ops.edge.quantized_decomposed.quantize_per_tensor(
92 nodes[0] == exir_ops.edge.quantized_decomposed.quantize_per_tensor
99 exir_ops.edge.quantized_decomposed.quantize_per_tensor.default,
154 exir_ops.edge.cadence.quantize_per_tensor.default,
161 exir_ops.edge.cadence.quantize_per_tensor.default,
/aosp_15_r20/external/pytorch/aten/src/ATen/test/
H A Dvulkan_quantized_api_test.cpp430 auto in_cpu_quantized = at::quantize_per_tensor( in TEST_F()
468 auto in_q_cpu = at::quantize_per_tensor(in_cpu, scale, zero_point, dtype); in test_cpu_to_vulkan_and_vulkan_to_cpu()
590 auto in_q_cpu = at::quantize_per_tensor(in_cpu, scale, zero_point, dtype); in test_cpu_to_vulkan_and_dequantize()
709 const auto out_cpu = at::quantize_per_tensor( in TEST_F()
711 const auto out_vulkan = at::native::vulkan::ops::quantize_per_tensor( in TEST_F()
742 at::quantize_per_tensor(input, input_scale, input_zero_point, dtype); in test_quantize_per_tensor_and_vulkan_to_cpu()
744 at::Tensor out_q_vk = at::quantize_per_tensor( in test_quantize_per_tensor_and_vulkan_to_cpu()
886 const auto out_cpu = at::quantize_per_tensor( in TEST_F()
888 const auto out_vulkan = at::native::vulkan::ops::quantize_per_tensor( in TEST_F()
931 ? at::quantize_per_tensor( in test_quantize_per_tensor_and_dequantize()
[all …]
/aosp_15_r20/external/pytorch/test/quantization/fx/
H A Dtest_equalize_fx.py619 ns.call_function(torch.quantize_per_tensor),
626 ns.call_function(torch.quantize_per_tensor),
631 ns.call_function(torch.quantize_per_tensor),
638 ns.call_function(torch.quantize_per_tensor),
646 ns.call_function(torch.quantize_per_tensor),
653 ns.call_function(torch.quantize_per_tensor),
658 ns.call_function(torch.quantize_per_tensor),
665 ns.call_function(torch.quantize_per_tensor),
673 ns.call_function(torch.quantize_per_tensor),
680 ns.call_function(torch.quantize_per_tensor),
[all …]
H A Dtest_quantize_fx.py538 ns.call_function(torch.quantize_per_tensor): 1 if two_conv else 2,
545 ns.call_function(torch.quantize_per_tensor): 3,
638 ns.call_function(torch.quantize_per_tensor),
644 ns.call_function(torch.quantize_per_tensor),
2000 ns.call_function(torch.quantize_per_tensor) : 1,
2007 ns.call_function(torch.quantize_per_tensor) : 1,
2034 ns.call_function(torch.quantize_per_tensor) : 1,
2042 ns.call_function(torch.quantize_per_tensor) : 0,
2077 ns.call_function(torch.quantize_per_tensor),
2106 ns.call_function(torch.quantize_per_tensor),
[all …]
/aosp_15_r20/external/pytorch/test/quantization/jit/
H A Dtest_ondevice_quantization.py98 weight.kind() != "aten::quantize_per_tensor"
116 weight.kind() != "aten::quantize_per_tensor"
119 return weight.kind() != "aten::quantize_per_tensor"
194 quantize_per_tensor = quantize_per_channel = 0
196 if "aten::quantize_per_tensor" in n.kind():
197 quantize_per_tensor += 1
200 self.assertEqual(quantize_per_tensor + quantize_per_channel, num_nodes)
261 quantize_per_tensor = quantize_per_channel = 0
276 quantize_per_tensor += 1
277 self.assertEqual(quantize_per_tensor + quantize_per_channel, num_nodes)
[all …]
H A Dtest_quantize_jit.py112 FileCheck().check_count("aten::quantize_per_tensor", 2, exactly=True).run(
119 FileCheck().check("aten::quantize_per_tensor").check_next(
124 "aten::quantize_per_tensor"
1062 else "aten::quantize_per_tensor"
1119 else "aten::quantize_per_tensor"
1170 x = torch.quantize_per_tensor(x, 0.5, 1, torch.quint8)
1196 x = torch.quantize_per_tensor(x, 0.5, 1, torch.quint8)
1222 x = torch.quantize_per_tensor(
1228 x = torch.quantize_per_tensor(x, scale=0.5, zero_point=1, dtype=torch.quint8)
1230 weight = torch.quantize_per_tensor(
[all …]
/aosp_15_r20/external/pytorch/torch/ao/quantization/fx/
H A DREADME.md335 …quantize_per_tensor = torch.quantize_per_tensor(x, linear_input_scale_0, linear_input_zero_point_0…
336 dequantize = quantize_per_tensor.dequantize(); quantize_per_tensor = None
340 …quantize_per_tensor_1 = torch.quantize_per_tensor(linear, linear_scale_0, linear_zero_point_0, tor…
382 The quantize operator we can choose from right now are: (quantize_per_tensor, quantize_per_channel,…
413 …quantize_per_tensor = torch.quantize_per_tensor(x, linear_input_scale_0, linear_input_zero_point_0…
414 linear = self.linear(quantize_per_tensor); quantize_per_tensor = None
426 dequantize -> float_op -> quantize_per_tensor
437 weight - quantize_per_tensor - dequantize /
H A D_decomposed.py45 "quantize_per_tensor(Tensor input, float scale, int zero_point, "
50 @impl(quantized_decomposed_lib, "quantize_per_tensor", "CompositeExplicitAutograd")
51 def quantize_per_tensor( function
87 @impl(quantized_decomposed_lib, "quantize_per_tensor", "Meta")
105 "quantize_per_tensor.tensor(Tensor input, Tensor scale, Tensor zero_point, "
111 quantized_decomposed_lib, "quantize_per_tensor.tensor", "CompositeExplicitAutograd"
123 Same as `quantize_per_tensor` but scale and zero_point are Scalar Tensor instead of
132 return quantize_per_tensor(
137 @impl(quantized_decomposed_lib, "quantize_per_tensor.tensor", "Meta")
162 "quantize_per_tensor.tensor2(Tensor input, Tensor scale, Tensor zero_point, "
[all …]
/aosp_15_r20/external/executorch/kernels/quantized/test/
H A Dtest_out_variants.py77 self.assertIsNotNone(ops.edge.quantized_decomposed.quantize_per_tensor.out)
78 fn = ops.edge.quantized_decomposed.quantize_per_tensor.default
81 out_variant.name(), "quantized_decomposed::quantize_per_tensor.out"
86 ops.edge.quantized_decomposed.quantize_per_tensor.Tensor_out
88 fn = ops.edge.quantized_decomposed.quantize_per_tensor.tensor
91 out_variant.name(), "quantized_decomposed::quantize_per_tensor.Tensor_out"
/aosp_15_r20/external/pytorch/test/mobile/model_test/
H A Dquantization_ops.py18 a = torch.quantize_per_tensor(torch.tensor([3.0]), 1.0, 0, torch.qint32)
19 b = torch.quantize_per_tensor(torch.tensor(4.0), 1.0, 0, torch.qint32)
20 c = torch.quantize_per_tensor(
35 torch.quantize_per_tensor(
40 torch.quantize_per_tensor(
45 …# self.conv3(torch.quantize_per_tensor(input3, scale=1.0, zero_point=0, dtype=torch.quint8)), # fa…
/aosp_15_r20/external/pytorch/torch/ao/quantization/pt2e/
H A Dutils.py25 torch.ops.quantized_decomposed.quantize_per_tensor.default,
26 torch.ops.quantized_decomposed.quantize_per_tensor.tensor,
404 …torch.ops.quantized_decomposed.quantize_per_tensor.default: torch.ops.quantized_decomposed.quantiz…
406 …torch.ops.quantized_decomposed.quantize_per_tensor.tensor: torch.ops.quantized_decomposed.quantize…
408 …torch.ops.quantized_decomposed.quantize_per_tensor.tensor2: torch.ops.quantized_decomposed.quantiz…
/aosp_15_r20/external/pytorch/torch/ao/nn/quantized/modules/
H A Dactivation.py40 >>> input = torch.quantize_per_tensor(input, 1.0, 0, dtype=torch.qint32)
262 bias_k = torch.quantize_per_tensor(bias_k, sc, zp, torch.quint8)
270 bias_v = torch.quantize_per_tensor(bias_v, sc, zp, torch.quint8)
296 qw = torch.quantize_per_tensor(w, scale=1.0, zero_point=0, dtype=torch.quint8)
322 qweight = torch.quantize_per_tensor(
339 qweight = torch.quantize_per_tensor(
/aosp_15_r20/external/pytorch/aten/src/ATen/native/vulkan/ops/
H A DQuantizedTensor.cpp31 Tensor quantize_per_tensor( in quantize_per_tensor() function
101 return quantize_per_tensor( in quantize_per_tensor_tensor_qparams()
185 TORCH_SELECTIVE_NAME("aten::quantize_per_tensor"), quantize_per_tensor); in TORCH_LIBRARY_IMPL()
187 TORCH_SELECTIVE_NAME("aten::quantize_per_tensor.tensor_qparams"), in TORCH_LIBRARY_IMPL()
/aosp_15_r20/external/executorch/backends/transforms/test/
H A Dtest_duplicate_dynamic_quant_chain.py97 torch.ops.quantized_decomposed.quantize_per_tensor.tensor: 2,
129 torch.ops.quantized_decomposed.quantize_per_tensor.tensor: 1,
137 torch.ops.quantized_decomposed.quantize_per_tensor.tensor: 2,
167 torch.ops.quantized_decomposed.quantize_per_tensor.tensor: 1,
175 torch.ops.quantized_decomposed.quantize_per_tensor.tensor: 1,
/aosp_15_r20/external/pytorch/torch/ao/quantization/pt2e/representation/
H A Drewrite.py73 out_i8 = torch.ops.quantized_decomposed.quantize_per_tensor(
161 x_i8 = torch.ops.quantized_decomposed.quantize_per_tensor(
194 # decomposed representation for quantize_per_tensor
290 out_i8 = torch.ops.quantized_decomposed.quantize_per_tensor(
412 out_i8 = torch.ops.quantized_decomposed.quantize_per_tensor(
474 out_i8 = torch.ops.quantized_decomposed.quantize_per_tensor(
556 out_i8 = torch.ops.quantized_decomposed.quantize_per_tensor(
600 x = torch.ops.quantized_decomposed.quantize_per_tensor(

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