Add custom ops ReplaceZero

operators/cuda/cuda_ops.cc

@@ -7,6 +7,7 @@
 #include "cuda/add_mul.h"
 #include "cuda/fast_gelu.h"
 #include "cuda/negxplus1.h"
+#include "cuda/replace_zero.h"
 #endif
 
 FxLoadCustomOpFactory LoadCustomOpClasses_Contrib = []() -> CustomOpArray& {
@@ -28,13 +29,15 @@ FxLoadCustomOpFactory LoadCustomOpClasses_Contrib = []() -> CustomOpArray& {
       CustomCudaStructV2("FastGelu", contrib::FastGelu<float>),
       CustomCudaStructV2("MulSharedInput", MulSharedInputFloat32Type),
       CustomCudaStructV2("NegXPlus1", contrib::NegXPlus1<float>),
+      CustomCudaStructV2("ReplaceZero", contrib::ReplaceZero<float>),
 #if ORT_API_VERSION >= 16
 
       CustomCudaStructV2("AddSharedInput", AddSharedInputFloat16Type),
       CustomCudaStructV2("FastGelu", contrib::FastGelu<ortc::MFloat16>),
       CustomCudaStructV2("FastGelu", contrib::FastGelu<ortc::BFloat16>),
       CustomCudaStructV2("MulSharedInput", MulSharedInputFloat16Type),
-      CustomCudaStructV2("NegXPlus1", contrib::NegXPlus1<ortc::MFloat16>)
+      CustomCudaStructV2("NegXPlus1", contrib::NegXPlus1<ortc::MFloat16>),
+      CustomCudaStructV2("ReplaceZero", contrib::ReplaceZero<ortc::MFloat16>)
 #endif
 #endif
   );

operators/cuda/replace_zero.h

@@ -0,0 +1,42 @@
+// Copyright (c) Microsoft Corporation. All rights reserved.
+// Licensed under the MIT License.
+
+#pragma once
+#include "ocos.h"
+#include "replace_zero_impl.cuh"
+#include "ortx_common.h"
+
+namespace contrib {
+
+template <typename T>
+struct ReplaceZero {
+  template <typename TDict>
+  OrtxStatus OnModelAttach(const TDict& dict) {
+    float default_value=0;
+    by_ = dict.TryToGetAttributeWithDefault("by", default_value);
+    return {};
+  }
+  OrtxStatus Compute(Ort::Custom::CUDAKernelContext* ctx,
+                       const ortc::Tensor<T>& input,
+                       ortc::Tensor<T>& output) const {
+    const T* input_data = input.Data();
+    auto input_shape = input.Shape();
+    T* output_data = output.Allocate(input_shape);
+    auto input_length = input.NumberOfElement();
+    if (0 == input_length) {
+      return {};
+    }
+
+    LaunchReplaceZeroKernel<T>(reinterpret_cast<cudaStream_t>(ctx->GetCudaStream()),
+                             input_length,
+                             input_data,
+                             output_data,
+                             by_);
+    return {};
+  }
+
+  private:
+  float by_;
+};
+
+}  // namespace contrib

operators/cuda/replace_zero_impl.cu

@@ -0,0 +1,64 @@
+// Copyright (c) Microsoft Corporation. All rights reserved.
+// Licensed under the MIT License.
+
+#include "device_prop.cuh"
+#include "utils.cuh"
+#include "replace_zero_impl.cuh"
+#include "cuda_type.h"
+
+#ifndef CUDA_LONG
+#define CUDA_LONG int32_t
+#endif
+
+using namespace Ort::Custom;
+
+template <typename T> __device__ __inline__ T _replace_zero(const T x, const T by) {
+  return x == (T)0 ? by : x;
+}
+
+template <> __device__ __inline__ half _replace_zero(const half x, const half by) {
+#if __CUDA_ARCH__ < 700
+  return __half2float(x) == 0 ? by : x;
+#else
+  return x == (half)0 ? by : x;
+#endif
+}
+
+template <typename T>
+__global__ void ReplaceZeroKernel(T *output_data, const T *input_data, CUDA_LONG N, const T by) {
+  CUDA_LONG id = blockDim.x * blockIdx.x + threadIdx.x;
+  if (id >= N)
+    return;
+  output_data[id] = _replace_zero(input_data[id], by);
+}
+
+template <typename T> T _cvt(float value) { return (T)value; }
+
+template <> half _cvt(float value) { return __float2half(value); }
+
+template <typename T>
+cudaError_t _LaunchReplaceZeroKernel(cudaStream_t stream, int input_length, const T* input_data, T* output_data, float by) {
+  if (input_length == 0)
+      return cudaGetLastError();
+  using TT = typename contrib::CudaT<T>::MappedType;
+
+  CUDA_LONG N = static_cast<CUDA_LONG>(input_length);
+
+  const int num_threads_per_block = 256;
+  const int num_elements_per_thread = (N + num_threads_per_block - 1) / num_threads_per_block;
+
+  TT cby = _cvt<TT>(by);
+  ReplaceZeroKernel<TT><<<num_elements_per_thread, num_threads_per_block, 0, stream>>>(
+    reinterpret_cast<TT*>(output_data), reinterpret_cast<const TT*>(input_data), N, cby);
+  return cudaGetLastError();
+}
+
+template <>
+cudaError_t LaunchReplaceZeroKernel<float>(cudaStream_t stream, int input_length, const float* input_data, float* output_data, float by) {
+  return _LaunchReplaceZeroKernel(stream, input_length, input_data, output_data, by);
+}
+
+template <>
+cudaError_t LaunchReplaceZeroKernel<ortc::MFloat16>(cudaStream_t stream, int input_length, const ortc::MFloat16* input_data, ortc::MFloat16* output_data, float by) {
+  return _LaunchReplaceZeroKernel(stream, input_length, input_data, output_data, by);
+}

operators/cuda/replace_zero_impl.cuh

@@ -0,0 +1,9 @@
+// Copyright (c) Microsoft Corporation. All rights reserved.
+// Licensed under the MIT License.
+
+#pragma once
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+template <typename T>
+cudaError_t LaunchReplaceZeroKernel(cudaStream_t stream, int input_length,  const T* input_data, T* output_data, float by);

test/cuda/test_cudaops.py

@@ -1,6 +1,6 @@
 import unittest
 import numpy as np
-from numpy.testing import assert_almost_equal
+from numpy.testing import assert_almost_equal, assert_allclose
 from onnx import helper, numpy_helper, onnx_pb as onnx_proto, TensorProto
 from onnx.reference import ReferenceEvaluator
 from onnx.reference.op_run import OpRun
@@ -151,7 +151,7 @@ def test_cuda_negxplus1(self):
         self._negxplus1_cuda(TensorProto.FLOAT16)
 
     def _addmul_shared_input_cuda(self, itype, op_type, shapea=(3, 2, 3), shapeb=(3, 2, 3), shapec=(3, 2, 3)):
-        from onnx_extended.ortops.optim.cuda import get_ort_ext_libs
+        from ai.onnx.contrib import get_ort_ext_libs
 
         model1 = helper.make_model(
             helper.make_graph(
@@ -181,7 +181,7 @@ def _addmul_shared_input_cuda(self, itype, op_type, shapea=(3, 2, 3), shapeb=(3,
                         f"{op_type}SharedInput",
                         ["X", "Y", "Z"],
                         ["XY", "XZ"],
-                        domain="onnx_extended.ortops.optim.cuda",
+                        domain="ai.onnx.contrib",
                     )
                 ],
                 "nd",
@@ -197,7 +197,7 @@ def _addmul_shared_input_cuda(self, itype, op_type, shapea=(3, 2, 3), shapeb=(3,
             ),
             opset_imports=[
                 helper.make_opsetid("", 18),
-                helper.make_opsetid("onnx_extended.ortops.optim.cuda", 1),
+                helper.make_opsetid("ai.onnx.contrib", 1),
             ],
             ir_version=9,
         )
@@ -262,6 +262,66 @@ def test_add_shared_input_cuda_broadcast2(self):
             shapec=(3, 2, 3),
         )
 
+    def _replace_zero_cuda(self, itype):
+        dtype = np.float32 if itype == TensorProto.FLOAT else np.float16
+        model1 = helper.make_model(
+            helper.make_graph(
+                [
+                    helper.make_node("Equal", ["X", "zero"], ["cond"]),
+                    helper.make_node("Where", ["cond", "cst", "X"], ["Y"]),
+                ],
+                "nd",
+                [helper.make_tensor_value_info("X", itype, [None, None, None])],
+                [helper.make_tensor_value_info("Y", itype, [None, None, None])],
+                [
+                    numpy_helper.from_array(np.array([0], dtype=dtype), name="zero"),
+                    numpy_helper.from_array(np.array([1.67], dtype=dtype), name="cst"),
+                ],
+            ),
+            opset_imports=[helper.make_opsetid("", 18)],
+            ir_version=9,
+        )
+
+        model2 = helper.make_model(
+            helper.make_graph(
+                [
+                    helper.make_node(
+                        "ReplaceZero",
+                        ["X"],
+                        ["Y"],
+                        by=1.67,
+                        domain="ai.onnx.contrib",
+                    )
+                ],
+                "nd",
+                [helper.make_tensor_value_info("X", itype, [None, None, None])],
+                [helper.make_tensor_value_info("Y", itype, [None, None, None])],
+            ),
+            opset_imports=[
+                helper.make_opsetid("", 18),
+                helper.make_opsetid("ai.onnx.contrib", 1),
+            ],
+            ir_version=9,
+        )
+
+        dtype = np.float32 if itype == TensorProto.FLOAT else np.float16
+        x = (np.arange(18) - 4).reshape((3, 2, 3)).astype(dtype)
+
+        feeds1 = dict(X=x)
+        ref = ReferenceEvaluator(model1)
+        expected = ref.run(None, feeds1)[0]
+
+        opts = _ort.SessionOptions()
+        opts.register_custom_ops_library(_get_library_path())
+        sess = _ort.InferenceSession(model2.SerializeToString(), opts, providers=["CUDAExecutionProvider"])
+        got = sess.run(None, feeds1)[0]
+        assert_allclose(expected, got, atol=1e-5)
+
+    @unittest.skipIf(not has_cuda(), reason="cuda not available")
+    def test_replace_zero_cuda(self):
+        self._replace_zero_cuda(TensorProto.FLOAT)
+        self._replace_zero_cuda(TensorProto.FLOAT16)
+
 
 if __name__ == "__main__":
     unittest.main()