From 47ab1762d1c15a7b4c0c068d7294111c5c5f92a2 Mon Sep 17 00:00:00 2001 From: evacha01 Date: Mon, 29 Jan 2024 13:23:23 +0000 Subject: Main Compliance testing for CONV3D Signed-off-by: evacha01 Change-Id: Ie05f88db15cd07fd5483ab669329d7048bd3349c --- .../src/generate/generate_dot_product.cc | 143 +++++++++++++++++++ reference_model/src/generate/generate_utils.cc | 1 + reference_model/test/generate_tests.cpp | 158 +++++++++++++++++++++ verif/conformance/tosa_main_profile_ops_info.json | 5 +- verif/generator/tosa_test_gen.py | 21 ++- 5 files changed, 320 insertions(+), 8 deletions(-) diff --git a/reference_model/src/generate/generate_dot_product.cc b/reference_model/src/generate/generate_dot_product.cc index 046007e..7337969 100644 --- a/reference_model/src/generate/generate_dot_product.cc +++ b/reference_model/src/generate/generate_dot_product.cc @@ -736,6 +736,147 @@ bool generateTransposeConv2D(const TosaReference::GenerateConfig& cfg, return false; } } + +//---------------------------------------------------------------------------// +// Conv3D // +//---------------------------------------------------------------------------// + +template +bool generateConv3DInput(const TosaReference::GenerateConfig& cfg, + TosaReference::IDotProductGenerator& generator, + DataType* data, + size_t size) +{ + if (cfg.dotProductInfo.kernel.size() != 3 || cfg.dotProductInfo.kernel[0] <= 0 || + cfg.dotProductInfo.kernel[1] <= 0 || cfg.dotProductInfo.kernel[2] <= 0) + { + WARNING("[Generator][DP][Conv3D][Input] Missing or incorrect kernel size information."); + return false; + } + if (cfg.shape.size() != 5) + { + WARNING("[Generator][DP][Conv3D][Input] Tensor shape expected 5 dimensions."); + return false; + } + + const int64_t T = TosaReference::numElementsFromShape(cfg.shape); + const uint32_t ID = cfg.shape[1]; + const uint32_t IH = cfg.shape[2]; + const uint32_t IW = cfg.shape[3]; + const uint32_t IC = cfg.shape[4]; + const uint32_t KD = cfg.dotProductInfo.kernel[0]; + const uint32_t KH = cfg.dotProductInfo.kernel[1]; + const uint32_t KW = cfg.dotProductInfo.kernel[2]; + + for (int64_t t = 0; t < T; ++t) + { + uint32_t ic = t % IC; + uint32_t ix = (t / IC) % IW; + uint32_t iy = ((t / IC) / IW) % IH; + uint32_t id = (((t / IC) / IW) / IH) % ID; + uint32_t k = (((id % KD) * KH + (iy % KH)) * KW + (ix % KW)) * IC + ic; + + data[t] = static_cast(generator(k)); + } + return true; +} + +template +bool generateConv3DWeight(const TosaReference::GenerateConfig& cfg, + TosaReference::IDotProductGenerator& generator, + DataType* data, + size_t size) +{ + if (cfg.shape.size() != 5) + { + WARNING("[Generator][DP][Conv3D][Weight] Tensor shape expected 5 dimensions."); + return false; + } + + const int64_t T = TosaReference::numElementsFromShape(cfg.shape); + const uint32_t KD = cfg.shape[0]; + const uint32_t KH = cfg.shape[1]; + const uint32_t KW = cfg.shape[2]; + const uint32_t IC = cfg.shape[3]; + + for (int64_t t = 0; t < T; ++t) + { + uint32_t ic = t % IC; + uint32_t kx = (t / IC) % KW; + uint32_t ky = ((t / IC) / KW) % KH; + uint32_t kd = (((t / IC) / KW) / KH) % KD; + uint32_t k = ((kd * KH + ky) * KW + kx) * IC + ic; + + data[t] = static_cast(generator(k)); + } + return true; +} + +template +bool generateConv3DBias(const TosaReference::GenerateConfig& cfg, + TosaReference::IDotProductGenerator& generator, + DataType* data, + size_t size) +{ + if (cfg.shape.size() != 1) + { + WARNING("[Generator][DP][Conv3D][Bias] Tensor shape expected 1 dimension."); + return false; + } + + const uint32_t T = cfg.shape[0]; + + for (uint32_t t = 0; t < T; ++t) + { + data[t] = static_cast(generator(2)); + } + return true; +} + +bool generateConv3D(const TosaReference::GenerateConfig& cfg, + TosaReference::IDotProductGenerator& generator, + void* data, + size_t size) +{ + switch (cfg.dataType) + { + case DType::DType_FP32: { + float* outData = reinterpret_cast(data); + switch (cfg.inputPos) + { + case 0: + return generateConv3DInput(cfg, generator, outData, size); + case 1: + return generateConv3DWeight(cfg, generator, outData, size); + case 2: + return generateConv3DBias(cfg, generator, outData, size); + default: + WARNING("[Generator][DP][Conv3D] Invalid input tensor slot position to operator."); + return false; + } + break; + } + case DType::DType_FP16: { + half_float::half* outData = reinterpret_cast(data); + switch (cfg.inputPos) + { + case 0: + return generateConv3DInput(cfg, generator, outData, size); + case 1: + return generateConv3DWeight(cfg, generator, outData, size); + case 2: + return generateConv3DBias(cfg, generator, outData, size); + default: + WARNING("[Generator][DP][Conv3D] Invalid input tensor slot position to operator."); + return false; + } + break; + } + default: + WARNING("[Generator][DP][Conv3D] Only supports FP32 or FP16."); + return false; + } +} //---------------------------------------------------------------------------// // FFT2D // //---------------------------------------------------------------------------// @@ -858,6 +999,8 @@ bool generateDotProduct(const GenerateConfig& cfg, void* data, size_t size) return generateDepthwiseConv2D(cfg, *generator, data, size); case tosa::Op_TRANSPOSE_CONV2D: return generateTransposeConv2D(cfg, *generator, data, size); + case tosa::Op_CONV3D: + return generateConv3D(cfg, *generator, data, size); case tosa::Op_FFT2D: return generateFFT2D(cfg, *generator, data, size); default: diff --git a/reference_model/src/generate/generate_utils.cc b/reference_model/src/generate/generate_utils.cc index 2e40b04..c495fb6 100644 --- a/reference_model/src/generate/generate_utils.cc +++ b/reference_model/src/generate/generate_utils.cc @@ -50,6 +50,7 @@ NLOHMANN_JSON_SERIALIZE_ENUM(Op, { Op::Op_CONST, "CONST" }, { Op::Op_CONV2D, "CONV2D" }, { Op::Op_DEPTHWISE_CONV2D, "DEPTHWISE_CONV2D" }, + { Op::Op_CONV3D, "CONV3D" }, { Op::Op_EQUAL, "EQUAL" }, { Op::Op_ERF, "ERF" }, { Op::Op_EXP, "EXP" }, diff --git a/reference_model/test/generate_tests.cpp b/reference_model/test/generate_tests.cpp index 4f62ede..3be402c 100644 --- a/reference_model/test/generate_tests.cpp +++ b/reference_model/test/generate_tests.cpp @@ -1224,6 +1224,164 @@ TEST_CASE("positive - FP16 transpose_conv2d dot product (last 3 values)") } } +void conv3d_test_FP16(const std::string tosaName[3], + const size_t tosaElements[3], + const std::string templateJsonCfg, + const std::string setStr, + int32_t param, + const std::vector expected) +{ + std::string jsonCfg = templateJsonCfg; + update_json_template(jsonCfg, "_SET_", setStr); + + std::vector buffer(tosaElements[param]); + REQUIRE(tgd_generate_data(jsonCfg.c_str(), tosaName[param].c_str(), (void*)buffer.data(), tosaElements[param] * 2)); + check_output(buffer, expected); +} + +TEST_CASE("positive - FP16 conv3d dot product (first 3 values)") +{ + std::string templateJsonCfg = R"({ + "tensors" : { + "input" : { + "generator": "DOT_PRODUCT", + "data_type": "FP16", + "input_type": "VARIABLE", + "shape" : [1, 3, 2, 2, 3], + "input_pos": 0, + "op" : "CONV3D", + "dot_product_info": { + "s": _SET_, + "ks": 27, + "acc_type": "FP16", + "kernel": [3, 1, 3] + } + }, + "weight" : { + "generator": "DOT_PRODUCT", + "data_type": "FP16", + "input_type": "CONSTANT", + "shape" : [4, 3, 1, 3, 3], + "input_pos": 1, + "op" : "CONV3D", + "dot_product_info": { + "s": _SET_, + "ks": 27, + "acc_type": "FP16" + } + }, + "bias" : { + "generator": "DOT_PRODUCT", + "data_type": "FP16", + "input_type": "CONSTANT", + "shape" : [ 4 ], + "input_pos": 2, + "op" : "CONV3D", + "dot_product_info": { + "s": _SET_, + "ks": 27, + "acc_type": "FP16" + } + } + + } + })"; + + const std::string tosaName[3] = { "input", "weight", "bias" }; + const size_t tosaElements[3] = { (1 * 3 * 2 * 2 * 3), (4 * 3 * 1 * 3 * 3), 4 }; + + SUBCASE("conv3d, set 0, param 0") + { + std::vector expected = { 0xbb33, 0xbb9b, 0x0 }; + conv3d_test_FP16(tosaName, tosaElements, templateJsonCfg, "0", 0, expected); + } + SUBCASE("conv3d, set 0, param 1") + { + std::vector expected = { 0x0, 0x0, 0x39a8 }; + conv3d_test_FP16(tosaName, tosaElements, templateJsonCfg, "0", 1, expected); + } + SUBCASE("conv3d, set 0, param 2") + { + std::vector expected = { 0x0, 0x0, 0x0 }; + conv3d_test_FP16(tosaName, tosaElements, templateJsonCfg, "0", 2, expected); + } + SUBCASE("conv3d, set 1, param 0") + { + std::vector expected = { 0x4e37, 0x4ed1, 0x4f87 }; + conv3d_test_FP16(tosaName, tosaElements, templateJsonCfg, "1", 0, expected); + } + SUBCASE("conv3d, set 1, param 1") + { + std::vector expected = { 0x51fe, 0x5104, 0x4fbf }; + conv3d_test_FP16(tosaName, tosaElements, templateJsonCfg, "1", 1, expected); + } + SUBCASE("conv3d, set 1, param 2") + { + std::vector expected = { 0x6498, 0x66e0, 0x687d }; + conv3d_test_FP16(tosaName, tosaElements, templateJsonCfg, "1", 2, expected); + } + SUBCASE("conv3d, set 2, param 0") + { + std::vector expected = { 0x3c00, 0x2bdb, 0xad62 }; + conv3d_test_FP16(tosaName, tosaElements, templateJsonCfg, "2", 0, expected); + } + SUBCASE("conv3d, set 2, param 1") + { + std::vector expected = { 0x3c00, 0x1814, 0x31be }; + conv3d_test_FP16(tosaName, tosaElements, templateJsonCfg, "2", 1, expected); + } + SUBCASE("conv3d, set 2, param 2") + { + std::vector expected = { 0x0, 0x0, 0x0 }; + conv3d_test_FP16(tosaName, tosaElements, templateJsonCfg, "2", 2, expected); + } + SUBCASE("conv3d, set 3, param 0") + { + std::vector expected = { 0x4c00, 0xb92b, 0x30f4 }; + conv3d_test_FP16(tosaName, tosaElements, templateJsonCfg, "3", 0, expected); + } + SUBCASE("conv3d, set 3, param 1") + { + std::vector expected = { 0x4c00, 0x3a2e, 0x3bf5 }; + conv3d_test_FP16(tosaName, tosaElements, templateJsonCfg, "3", 1, expected); + } + SUBCASE("conv3d, set 3, param 2") + { + std::vector expected = { 0x0, 0x0, 0x0 }; + conv3d_test_FP16(tosaName, tosaElements, templateJsonCfg, "3", 2, expected); + } + SUBCASE("conv3d, set 4, param 0") + { + std::vector expected = { 0x0, 0x0, 0x5110 }; + conv3d_test_FP16(tosaName, tosaElements, templateJsonCfg, "4", 0, expected); + } + SUBCASE("conv3d, set 4, param 1") + { + std::vector expected = { 0x4384, 0xd1de, 0x0 }; + conv3d_test_FP16(tosaName, tosaElements, templateJsonCfg, "4", 1, expected); + } + SUBCASE("conv3d, set 4, param 2") + { + std::vector expected = { 0x0, 0x0, 0x0 }; + conv3d_test_FP16(tosaName, tosaElements, templateJsonCfg, "4", 2, expected); + } + SUBCASE("conv3d, set 5, param 0") + { + std::vector expected = { 0x490c, 0x4ccf, 0x5046 }; + conv3d_test_FP16(tosaName, tosaElements, templateJsonCfg, "5", 0, expected); + } + SUBCASE("conv3d, set 5, param 1") + { + std::vector expected = { 0xc994, 0x4ca4, 0x4f9f }; + conv3d_test_FP16(tosaName, tosaElements, templateJsonCfg, "5", 1, expected); + } + SUBCASE("conv3d, set 5, param 2") + { + std::vector expected = { 0x0, 0x0, 0x0 }; + conv3d_test_FP16(tosaName, tosaElements, templateJsonCfg, "5", 2, expected); + } +} + void fft2d_test_FP32(const std::string tosaName, const size_t tosaElements, const std::string templateJsonCfg, diff --git a/verif/conformance/tosa_main_profile_ops_info.json b/verif/conformance/tosa_main_profile_ops_info.json index 067fab7..a53d0c7 100644 --- a/verif/conformance/tosa_main_profile_ops_info.json +++ b/verif/conformance/tosa_main_profile_ops_info.json @@ -684,6 +684,7 @@ "profile": [ "tosa-mi" ], + "support_for": [ "lazy_data_gen" ], "generation": { "standard": { "negative_dim_range": "1,10", @@ -696,7 +697,7 @@ "--target-dtype", "bf16", "--fp-values-range", - "-2.0,2.0", + "-max,max", "--target-shape", "1,7,18,5,4", "--target-shape", @@ -709,7 +710,7 @@ "--target-dtype", "fp32", "--fp-values-range", - "-2.0,2.0", + "-max,max", "--target-shape", "1,2,65539,1,2", "--target-shape", diff --git a/verif/generator/tosa_test_gen.py b/verif/generator/tosa_test_gen.py index 68a4e94..9c3cd32 100644 --- a/verif/generator/tosa_test_gen.py +++ b/verif/generator/tosa_test_gen.py @@ -325,6 +325,7 @@ class TosaTestGen: Op.FULLY_CONNECTED, Op.DEPTHWISE_CONV2D, Op.TRANSPOSE_CONV2D, + Op.CONV3D, ) if ( errorName @@ -952,7 +953,7 @@ class TosaTestGen: dilations = args_dict["dilation"] assert len(padding) == 6 - result_tens = OutputShaper.conv3dOp( + result_tensor = OutputShaper.conv3dOp( self.ser, self.rng, ifm, @@ -971,12 +972,12 @@ class TosaTestGen: ): qinfo = [ TosaQuantGen.getZeroPoint(self, ifm.dtype), - TosaQuantGen.getZeroPoint(self, result_tens.dtype), + TosaQuantGen.getZeroPoint(self, result_tensor.dtype), ] # Invalidate Input/Output list for error_if checks. input_list = [ifm.name, filter.name, bias.name] - output_list = [result_tens.name] + output_list = [result_tensor.name] num_operands = sum(op["operands"]) input_list, output_list = TosaErrorIfArgGen.eiInvalidateInputOutputList( self, error_name, input_list, output_list @@ -989,7 +990,7 @@ class TosaTestGen: op=op, input_dtype=ifm.dtype, weight_dtype=filter.dtype, - output_dtype=result_tens.dtype, + output_dtype=result_tensor.dtype, qinfo=qinfo, input_list=input_list, num_operands=num_operands, @@ -999,7 +1000,7 @@ class TosaTestGen: dilation=dilations, input_shape=ifm.shape, weight_shape=filter.shape, - output_shape=result_tens.shape, + output_shape=result_tensor.shape, ): return None @@ -1010,7 +1011,12 @@ class TosaTestGen: attr.ConvAttribute(padding, strides, dilations, qinfo[0], qinfo[1], local_bound) self.ser.addOperator(op["op"], input_list, output_list, attr) - return result_tens + + compliance = self.tensorComplianceMetaData( + op, ifm.dtype, args_dict, result_tensor, error_name + ) + + return TosaTestGen.BuildInfo(result_tensor, compliance) def build_transpose_conv2d( self, @@ -3254,6 +3260,9 @@ class TosaTestGen: TosaErrorValidator.evConvOutputShapeMismatch, TosaErrorValidator.evConvOutputShapeNonInteger, ), + "data_gen": { + "fp": (gtu.DataGenType.DOT_PRODUCT,), + }, "template": True, }, # Templated operator. Filled in by createDynamicOpLists -- cgit v1.2.1