diff --git a/paddle/function/BufferArg.h b/paddle/function/BufferArg.h index 6576d18dae99e6f7c4abd8d388e420c22468e129..9649913fa8d9bf82b67fc2ac97ae9f30e7029528 100644 --- a/paddle/function/BufferArg.h +++ b/paddle/function/BufferArg.h @@ -126,7 +126,7 @@ public: CHECK(buf_); CHECK(valueType_ == DataType::value); // CHECK(deviceType_ == DType); - CHECK_EQ(2, shape_.ndims()); + CHECK_EQ((size_t)2, shape_.ndims()); return typename Tensor::Matrix( reinterpret_cast(buf_), shape_[0], shape_[1]); } @@ -136,7 +136,7 @@ public: CHECK(buf_); CHECK(valueType_ == DataType::value); // CHECK(deviceType_ == DType); - CHECK_EQ(1, shape_.ndims()); + CHECK_EQ((size_t)1, shape_.ndims()); return typename Tensor::Vector( shape_[0], reinterpret_cast(buf_)); } @@ -176,7 +176,7 @@ public: const TensorShape& shape, ArgType argType = UNSPECIFIED) : BufferArg(buf, VALUE_TYPE_INT32, shape, argType) { - CHECK_EQ(shape_.ndims(), 1); + CHECK_EQ(shape_.ndims(), (size_t)1); numSeqs_ = shape_[0] - 1; } @@ -238,9 +238,9 @@ public: format_(format), type_(type) { CHECK((valueType == VALUE_TYPE_FLOAT) || (valueType == VALUE_TYPE_DOUBLE)); - CHECK_EQ(shape_.ndims(), 2); - CHECK_EQ(row_.shape().ndims(), 1); - CHECK_EQ(col_.shape().ndims(), 1); + CHECK_EQ(shape_.ndims(), (size_t)2); + CHECK_EQ(row_.shape().ndims(), (size_t)1); + CHECK_EQ(col_.shape().ndims(), (size_t)1); if (format == SPARSE_CSR_FORMAT) { CHECK_EQ(nnz, col.shape()[0]); } else if (format == SPARSE_CSC_FORMAT) { diff --git a/paddle/function/ContextProjectionOp.cpp b/paddle/function/ContextProjectionOp.cpp index ca7a11f93683f68669aa9e22b32f12bb712e9522..cb448562ebb37022f727ee65024f06f69d63e9cb 100644 --- a/paddle/function/ContextProjectionOp.cpp +++ b/paddle/function/ContextProjectionOp.cpp @@ -85,8 +85,8 @@ public: } void calc(const BufferArgs& inputs, const BufferArgs& outputs) override { - CHECK_EQ(3, inputs.size()); - CHECK_EQ(1, outputs.size()); + CHECK_EQ((size_t)3, inputs.size()); + CHECK_EQ((size_t)1, outputs.size()); CHECK(outputs[0].data() && inputs[0].data() && inputs[2].data()); CHECK_EQ(outputs[0].shape().ndims(), (size_t)2); @@ -193,8 +193,8 @@ public: } void calc(const BufferArgs& inputs, const BufferArgs& outputs) override { - CHECK_EQ(3, inputs.size()); - CHECK_EQ(1, outputs.size()); + CHECK_EQ((size_t)3, inputs.size()); + CHECK_EQ((size_t)1, outputs.size()); CHECK(outputs[0].data() && inputs[2].data()); CHECK_EQ(outputs[0].shape().ndims(), (size_t)2); diff --git a/paddle/function/CrossMapNormalOp.cpp b/paddle/function/CrossMapNormalOp.cpp index cf989468403d266f4b93de8bc6bbaae7bc97f6a0..92980c503fdaaaa9ac600070197dba6ba4bfb7a4 100644 --- a/paddle/function/CrossMapNormalOp.cpp +++ b/paddle/function/CrossMapNormalOp.cpp @@ -131,7 +131,7 @@ public: CHECK_EQ((size_t)1, inputs.size()); CHECK_EQ((size_t)2, outputs.size()); - CHECK_EQ(inputs[0].shape().ndims(), 4); + CHECK_EQ(inputs[0].shape().ndims(), (size_t)4); CHECK(inputs[0].shape() == outputs[0].shape()); CHECK(inputs[0].shape() == outputs[1].shape()); @@ -182,7 +182,7 @@ public: CHECK_EQ((size_t)4, inputs.size()); CHECK_EQ((size_t)1, outputs.size()); - CHECK_EQ(inputs[0].shape().ndims(), 4); + CHECK_EQ(inputs[0].shape().ndims(), (size_t)4); CHECK(inputs[0].shape() == inputs[1].shape()); CHECK(inputs[0].shape() == inputs[2].shape()); CHECK(inputs[0].shape() == inputs[3].shape()); diff --git a/paddle/function/TensorShape.h b/paddle/function/TensorShape.h index 0333fe18316ba4a82bbdc2b1ef99e6d2186a234c..e491e3f1d6b26e14a5273b3b5a38aec941f5a9e5 100644 --- a/paddle/function/TensorShape.h +++ b/paddle/function/TensorShape.h @@ -42,14 +42,14 @@ public: // get the size of specified dimension size_t operator[](size_t dim) const { - CHECK_GE(dim, 0); + CHECK_GE(dim, (size_t)0); CHECK_LT(dim, ndims_); return dims_[dim]; } // set the size of specified dimension void setDim(size_t dim, size_t size) { - CHECK_GE(dim, 0); + CHECK_GE(dim, (size_t)0); CHECK_LT(dim, ndims_); dims_[dim] = size; numElements();