diff options
-rw-r--r-- | reference_model/src/generate/generate_dot_product.cc | 59 | ||||
-rw-r--r-- | reference_model/src/generate/generate_utils.cc | 1 | ||||
-rw-r--r-- | reference_model/src/ops/tensor_ops.cc | 45 | ||||
-rw-r--r-- | reference_model/test/generate_tests.cpp | 56 | ||||
-rw-r--r-- | verif/conformance/tosa_main_profile_ops_info.json | 5 | ||||
-rw-r--r-- | verif/generator/tosa_arg_gen.py | 25 | ||||
-rw-r--r-- | verif/generator/tosa_test_gen.py | 22 |
7 files changed, 202 insertions, 11 deletions
diff --git a/reference_model/src/generate/generate_dot_product.cc b/reference_model/src/generate/generate_dot_product.cc index 7337969..117d49d 100644 --- a/reference_model/src/generate/generate_dot_product.cc +++ b/reference_model/src/generate/generate_dot_product.cc @@ -963,6 +963,63 @@ bool generateFFT2D(const TosaReference::GenerateConfig& cfg, return true; } +//---------------------------------------------------------------------------// +// RFFT2D // +//---------------------------------------------------------------------------// + +template <typename DataType> +bool generateRFFT2DReal(const TosaReference::GenerateConfig& cfg, + TosaReference::IDotProductGenerator& generator, + DataType* data, + size_t size) +{ + const int64_t T = TosaReference::numElementsFromShape(cfg.shape); + const uint32_t H = cfg.shape[1]; + const uint32_t W = cfg.shape[2]; + + for (int64_t t = 0; t < T; ++t) + { + uint32_t x = t % W; + uint32_t y = (t / W) % H; + uint32_t k = y * W + x; + + data[t] = static_cast<DataType>(generator(k)); + } + return true; +} + +bool generateRFFT2D(const TosaReference::GenerateConfig& cfg, + TosaReference::IDotProductGenerator& generator, + void* data, + size_t size) +{ + if (cfg.shape.size() != 3) + { + WARNING("[Generator][DP][RFFT2D] Tensor shape expected 3 dimensions."); + return false; + } + + switch (cfg.dataType) + { + case DType::DType_FP32: { + float* outData = reinterpret_cast<float*>(data); + switch (cfg.inputPos) + { + case 0: + return generateRFFT2DReal(cfg, generator, outData, size); + default: + WARNING("[Generator][DP][RFFT2D] Invalid input tensor slot position to operator."); + return false; + } + break; + } + default: + WARNING("[Generator][DP][RFFT2D] Only supports FP32."); + return false; + } + + return true; +} } // namespace namespace TosaReference @@ -1003,6 +1060,8 @@ bool generateDotProduct(const GenerateConfig& cfg, void* data, size_t size) return generateConv3D(cfg, *generator, data, size); case tosa::Op_FFT2D: return generateFFT2D(cfg, *generator, data, size); + case tosa::Op_RFFT2D: + return generateRFFT2D(cfg, *generator, data, size); default: WARNING("[Generator][DP] Unsupported operator."); return false; diff --git a/reference_model/src/generate/generate_utils.cc b/reference_model/src/generate/generate_utils.cc index c495fb6..cf5308b 100644 --- a/reference_model/src/generate/generate_utils.cc +++ b/reference_model/src/generate/generate_utils.cc @@ -78,6 +78,7 @@ NLOHMANN_JSON_SERIALIZE_ENUM(Op, { Op::Op_REDUCE_PRODUCT, "REDUCE_PRODUCT" }, { Op::Op_REDUCE_SUM, "REDUCE_SUM" }, { Op::Op_REVERSE, "REVERSE" }, + { Op::Op_RFFT2D, "RFFT2D" }, { Op::Op_SCATTER, "SCATTER" }, { Op::Op_SELECT, "SELECT" }, { Op::Op_SIGMOID, "SIGMOID" }, diff --git a/reference_model/src/ops/tensor_ops.cc b/reference_model/src/ops/tensor_ops.cc index 8d8dac7..dd66f79 100644 --- a/reference_model/src/ops/tensor_ops.cc +++ b/reference_model/src/ops/tensor_ops.cc @@ -1820,6 +1820,9 @@ int OpRFFT2d<Dtype>::eval() int32_t out_imag_height = out_imag->getShape()[1]; int32_t out_imag_width = out_imag->getShape()[2]; + int32_t half_in_height = in_height / 2; + int32_t half_in_width = in_width / 2; + // Check Tosa Level auto tosa_level = g_func_config.tosa_level; LEVEL_CHECK(in_height <= tosa_level.MAX_KERNEL, "H should be smaller than or equal to MAX_KERNEL"); @@ -1831,7 +1834,8 @@ int OpRFFT2d<Dtype>::eval() in_batch, in_height, in_width, out_real_batch, out_real_height, out_real_width, out_imag_batch, out_imag_height, out_imag_width); - OutEigenType sum_real, sum_imag, a; + OutEigenType sum_real, sum_imag; + OutEigenType a, a_cos, a_sin, v_ir; TIn in_val = this->in->getTensor(); @@ -1853,10 +1857,41 @@ int OpRFFT2d<Dtype>::eval() { for (int ix = 0; ix < in_width; ix++) { - // Use explicit cast to ensure intermmediate calculations are completed using OutEigenType - a = 2 * M_PI * ((iy * (OutEigenType)oy) / in_height + (ix * (OutEigenType)ox) / in_width); - sum_real += in_val(n, iy, ix) * cos(a); - sum_imag += -in_val(n, iy, ix) * sin(a); + OutEigenType val = in_val(n, iy, ix); + // Perform the periodic calculation in integer maths to keep + // the accuracy of the co-efficients similar for FP32 normal + // and FP64 precise mode + int32_t ay = (static_cast<int64_t>(iy) * static_cast<int64_t>(oy)) % in_height; + int32_t ax = (static_cast<int64_t>(ix) * static_cast<int64_t>(ox)) % in_width; + + // Use explicit cast to ensure intermediate calculations are completed using OutEigenType + a = 2 * M_PI * ((OutEigenType)ay / in_height + (OutEigenType)ax / in_width); + + // Calculate weight values (co-efficients) + a_cos = cos(a); + a_sin = sin(a); + + if (g_func_config.abs_mode) + { + // Bounded op - Use abs weight values + a_cos = std::abs(a_cos); + a_sin = std::abs(a_sin); + // Bounded op - Use abs real value for imaginary calc + v_ir = val; + } + else + { + // Normal op - Use negative real value for imaginary calc + v_ir = -val; + } + sum_real += val * a_cos; + // Imaginary values with locations (0,0), (0,W/2), (H/2,0) and (H/2,W/2) are zero. + // But due to sin(M_PI) not returning 0 because of M_PI being approximate, only + // add to the imaginary sum when not processing these locations. + if ((ay % (half_in_height)) + (ax % (half_in_width)) > 0) + { + sum_imag += v_ir * a_sin; + } } } this->out_real->getTensor()(n, oy, ox) = sum_real; diff --git a/reference_model/test/generate_tests.cpp b/reference_model/test/generate_tests.cpp index 3be402c..564af4a 100644 --- a/reference_model/test/generate_tests.cpp +++ b/reference_model/test/generate_tests.cpp @@ -1500,4 +1500,60 @@ TEST_CASE("positive - FP32 fft2d dot product (values -8, -7 & -6 from the end)") } } +TEST_CASE("positive - FP32 rfft2d dot product (values -8, -7 & -6 from the end)") +{ + std::string templateJsonCfg = R"({ + "tensors" : { + "real" : { + "generator": "DOT_PRODUCT", + "data_type": "FP32", + "input_type": "VARIABLE", + "shape" : [ 4, 2, 4 ], + "input_pos": 0, + "op" : "FFT2D", + "dot_product_info": { + "s": _SET_, + "ks": 8, + "acc_type": "FP32" + } + } + } + })"; + + const std::string tosaNameReal = "real"; + const size_t tosaElements = 4 * 2 * 4; + + SUBCASE("fft2d, set 0, real") + { + std::vector<uint32_t> expected = { 0xbe14f2f5, 0xbdb6fe4d, 0x3f30b473 }; + fft2d_test_FP32(tosaNameReal, tosaElements, templateJsonCfg, "0", expected); + } + SUBCASE("fft2d, set 1, real") + { + // NOTE: Python test script produced 0x5e7219eb - so off by 1 + std::vector<uint32_t> expected = { 0x5e490017, 0x5e57dd30, 0x5e992496 }; + fft2d_test_FP32(tosaNameReal, tosaElements, templateJsonCfg, "1", expected); + } + SUBCASE("fft2d, set 2, real") + { + std::vector<uint32_t> expected = { 0x3f800000, 0xbe7f1cd4, 0xbdfc67ff }; + fft2d_test_FP32(tosaNameReal, tosaElements, templateJsonCfg, "2", expected); + } + SUBCASE("fft2d, set 3, real") + { + std::vector<uint32_t> expected = { 0x41800000, 0xbf6d219b, 0x3f2bd153 }; + fft2d_test_FP32(tosaNameReal, tosaElements, templateJsonCfg, "3", expected); + } + SUBCASE("fft2d, set 4, real") + { + std::vector<uint32_t> expected = { 0x0, 0x0, 0x0 }; + fft2d_test_FP32(tosaNameReal, tosaElements, templateJsonCfg, "4", expected); + } + SUBCASE("fft2d, set 5, real") + { + std::vector<uint32_t> expected = { 0xdd3f6b86, 0xde49ecfd, 0x5e0be03d }; + fft2d_test_FP32(tosaNameReal, tosaElements, templateJsonCfg, "5", expected); + } +} + TEST_SUITE_END(); // generate diff --git a/verif/conformance/tosa_main_profile_ops_info.json b/verif/conformance/tosa_main_profile_ops_info.json index a53d0c7..b8efd35 100644 --- a/verif/conformance/tosa_main_profile_ops_info.json +++ b/verif/conformance/tosa_main_profile_ops_info.json @@ -2702,6 +2702,7 @@ "profile": [ "tosa-mi" ], + "support_for": [ "lazy_data_gen" ], "generation": { "standard": { "generator_args": [ @@ -2709,13 +2710,13 @@ "--target-dtype", "fp32", "--fp-values-range", - "-2.0,2.0" + "-max,max" ], [ "--target-dtype", "fp32", "--fp-values-range", - "-2.0,2.0", + "-max,max", "--target-shape", "1,16,512", "--target-shape", diff --git a/verif/generator/tosa_arg_gen.py b/verif/generator/tosa_arg_gen.py index f6a46b4..a4bced3 100644 --- a/verif/generator/tosa_arg_gen.py +++ b/verif/generator/tosa_arg_gen.py @@ -2821,6 +2821,31 @@ class TosaArgGen: # Return list of tuples: (arg_str, args_dict) return arg_list + @staticmethod + def agRFFT2d(testGen, opName, shapeList, dtype, error_name=None): + arg_list = [] + + shape = shapeList[0] + dot_products = gtu.product(shape) + ks = shape[1] * shape[2] # H*W + args_dict = { + "dot_products": dot_products, + "shape": shape, + "ks": ks, + "acc_type": dtype, + } + arg_list.append(("", args_dict)) + + arg_list = TosaArgGen._add_data_generators( + testGen, + opName, + dtype, + arg_list, + error_name, + ) + # Return list of tuples: (arg_str, args_dict) + return arg_list + # Helper function for reshape. Gets some factors of a larger number. @staticmethod def getFactors(val, start=1): diff --git a/verif/generator/tosa_test_gen.py b/verif/generator/tosa_test_gen.py index 9c3cd32..d82f919 100644 --- a/verif/generator/tosa_test_gen.py +++ b/verif/generator/tosa_test_gen.py @@ -2588,10 +2588,14 @@ class TosaTestGen: def build_rfft2d( self, op, - val, + inputs, + args_dict, validator_fcns=None, error_name=None, + qinfo=None, ): + assert len(inputs) == 1 + val = inputs[0] results = OutputShaper.rfft2dOp(self.ser, self.rng, val, error_name) input_names = [val.name] @@ -2629,7 +2633,14 @@ class TosaTestGen: attr.RFFTAttribute(local_bound) self.ser.addOperator(op["op"], input_names, output_names, attr) - return results + + compliance = [] + for res in results: + compliance.append( + self.tensorComplianceMetaData(op, val.dtype, args_dict, res, error_name) + ) + + return TosaTestGen.BuildInfo(results, compliance) def build_shape_op( self, op, inputs, args_dict, validator_fcns=None, error_name=None, qinfo=None @@ -4781,8 +4792,8 @@ class TosaTestGen: "build_fcn": ( build_rfft2d, TosaTensorGen.tgRFFT2d, - TosaTensorValuesGen.tvgDefault, - None, + TosaTensorValuesGen.tvgLazyGenDefault, + TosaArgGen.agRFFT2d, ), "types": [DType.FP32], "error_if_validators": ( @@ -4795,6 +4806,9 @@ class TosaTestGen: TosaErrorValidator.evKernelNotPowerOfTwo, TosaErrorValidator.evFFTOutputShapeMismatch, ), + "data_gen": { + "fp": (gtu.DataGenType.DOT_PRODUCT,), + }, }, # Shape "add_shape": { |