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【PTen】Remove MakePtenDenseTensor in Op compute #38910

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merged 2 commits into from
Jan 17, 2022
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【PTen】Remove MakePtenDenseTensor in Op compute #38910

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66e8e22
remove MakePtenDenseTensor in op compute
zyfncg Jan 12, 2022
46efe37
Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into…
zyfncg Jan 15, 2022
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5 changes: 1 addition & 4 deletions paddle/fluid/operators/cast_op.h
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Original file line number Diff line number Diff line change
Expand Up @@ -63,14 +63,11 @@ class CastOpKernel : public framework::OpKernel<InT> {
out->mutable_data(dev_ctx.GetPlace(),
static_cast<framework::proto::VarType::Type>(out_dtype));

auto pt_x = paddle::experimental::MakePtenDenseTensor(*in);
auto pt_out = paddle::experimental::MakePtenDenseTensor(*out);

auto pt_out_dtype = pten::TransToPtenDataType(
static_cast<framework::proto::VarType::Type>(out_dtype));

// call new kernel
pten::CastKernel<InT>(dev_ctx, *pt_x.get(), pt_out_dtype, pt_out.get());
pten::CastKernel<InT>(dev_ctx, *in, pt_out_dtype, out);
}
};

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5 changes: 1 addition & 4 deletions paddle/fluid/operators/cholesky_solve_op.h
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Expand Up @@ -202,10 +202,7 @@ class CholeskySolveGradKernel : public framework::OpKernel<T> {
commonterm_for_range(commonterm_functor);
commonterm_conj = helper.Transpose(commonterm_conj);

auto pt_x = paddle::experimental::MakePtenDenseTensor(commonterm);
auto pt_y = paddle::experimental::MakePtenDenseTensor(commonterm_conj);
auto pt_z = paddle::experimental::MakePtenDenseTensor(commonterm);
pten::AddKernel<T>(dev_ctx, *pt_x.get(), *pt_y.get(), -1, pt_z.get());
pten::AddKernel<T>(dev_ctx, commonterm, commonterm_conj, -1, &commonterm);

auto mat_dim_u = math::CreateMatrixDescriptor(u_bst.dims(), 0, false);
auto mat_dim_c =
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4 changes: 1 addition & 3 deletions paddle/fluid/operators/conj_op.h
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Expand Up @@ -34,11 +34,9 @@ class ConjKernel : public framework::OpKernel<T> {
out->mutable_data<T>(context.GetPlace(), size_t(x->numel() * sizeof(T)));

auto& dev_ctx = context.device_context<DeviceContext>();
auto pt_x = paddle::experimental::MakePtenDenseTensor(*x);
auto pt_out = paddle::experimental::MakePtenDenseTensor(*out);

// call new kernel
pten::ConjKernel<T>(dev_ctx, *pt_x.get(), pt_out.get());
pten::ConjKernel<T>(dev_ctx, *x, out);
}
};

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17 changes: 3 additions & 14 deletions paddle/fluid/operators/dot_op.h
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Expand Up @@ -40,13 +40,8 @@ class DotKernel : public framework::OpKernel<T> {
auto& dev_ctx = ctx.device_context<DeviceContext>();
out->mutable_data<T>(x->place());

auto pt_x = paddle::experimental::MakePtenDenseTensor(*x);
auto pt_y = paddle::experimental::MakePtenDenseTensor(*y);
auto pt_out = paddle::experimental::MakePtenDenseTensor(*out);

// call new kernel
pten::DotKernel<T, DeviceContext>(dev_ctx, *pt_x.get(), *pt_y.get(),
pt_out.get());
pten::DotKernel<T, DeviceContext>(dev_ctx, *x, *y, out);
}
};

Expand All @@ -63,17 +58,11 @@ class DotGradKernel : public framework::OpKernel<T> {
if (tensor_dx) tensor_dx->mutable_data<T>(ctx.GetPlace());
if (tensor_dy) tensor_dy->mutable_data<T>(ctx.GetPlace());

auto pt_x = paddle::experimental::MakePtenDenseTensor(*tensor_x);
auto pt_y = paddle::experimental::MakePtenDenseTensor(*tensor_y);
auto pt_dout = paddle::experimental::MakePtenDenseTensor(*tensor_dout);
auto pt_dx = paddle::experimental::MakePtenDenseTensor(*tensor_dx);
auto pt_dy = paddle::experimental::MakePtenDenseTensor(*tensor_dy);

auto& dev_ctx = ctx.device_context<DeviceContext>();

// call new kernel
pten::DotGradKernel<T>(dev_ctx, *pt_x, *pt_y, *pt_dout, pt_dx.get(),
pt_dy.get());
pten::DotGradKernel<T>(dev_ctx, *tensor_x, *tensor_y, *tensor_dout,
tensor_dx, tensor_dy);
}
};

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4 changes: 1 addition & 3 deletions paddle/fluid/operators/fill_any_like_op.h
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Expand Up @@ -60,11 +60,9 @@ class FillAnyLikeKernel : public framework::OpKernel<T> {
std::isnan(value), false,
platform::errors::InvalidArgument("The filled value is NaN."));

auto pt_out = paddle::experimental::MakePtenDenseTensor(*out);

const auto& dev_ctx = context.template device_context<DeviceContext>();
// call new kernel
pten::FullLikeKernel<T>(dev_ctx, value, pt_out.get());
pten::FullLikeKernel<T>(dev_ctx, value, out);
}
};

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21 changes: 3 additions & 18 deletions paddle/fluid/operators/flatten_op.h
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Expand Up @@ -131,12 +131,9 @@ class FlattenContiguousRangeKernel : public framework::OpKernel<T> {
auto &stop_axis = context.Attr<int>("stop_axis");
auto &dev_ctx = context.device_context<DeviceContext>();

auto pt_x = paddle::experimental::MakePtenDenseTensor(*in);
auto pt_out = paddle::experimental::MakePtenDenseTensor(*out);

// call new kernel
pten::FlattenKernel<T, DeviceContext>(dev_ctx, *pt_x.get(), start_axis,
stop_axis, pt_out.get());
pten::FlattenKernel<T, DeviceContext>(dev_ctx, *in, start_axis, stop_axis,
out);
}
};

Expand All @@ -152,20 +149,8 @@ class FlattenContiguousRangeGradKernel : public framework::OpKernel<T> {
d_x->mutable_data(ctx.GetPlace(), d_out->type());
auto &dev_ctx = ctx.device_context<DeviceContext>();

auto pt_d_x = paddle::experimental::MakePtenDenseTensor(*d_x);
auto pt_d_out = paddle::experimental::MakePtenDenseTensor(*d_out);

// Because the holder of xshape may be nullptr, we can't use
// MakePtenDenseTensor.
// So, we create a new DenseTensor to save the dims of xshape.
pten::DenseTensorMeta xshape_meta{pten::TransToPtenDataType(d_x->type()),
xshape->dims(), d_x->layout()};
auto pt_xshape =
pten::Empty<T, DeviceContext>(dev_ctx, std::move(xshape_meta));

// call new kernel
pten::FlattenGradKernel<T, DeviceContext>(dev_ctx, *pt_d_out.get(),
pt_xshape, pt_d_x.get());
pten::FlattenGradKernel<T, DeviceContext>(dev_ctx, *d_out, *xshape, d_x);
}
};

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14 changes: 4 additions & 10 deletions paddle/fluid/operators/lu_op.h
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Expand Up @@ -220,23 +220,17 @@ void Tensor_Add(const DeviceContext& dev_ctx, const framework::Tensor& src1,
const framework::Tensor& src2, framework::Tensor* out) {
out->Resize(src1.dims());
out->mutable_data<T>(dev_ctx.GetPlace());
auto pt_x = paddle::experimental::MakePtenDenseTensor(src1);
auto pt_y = paddle::experimental::MakePtenDenseTensor(src2);
auto pt_z = paddle::experimental::MakePtenDenseTensor(*out);
pten::AddKernel<T, DeviceContext>(dev_ctx, *pt_x.get(), *pt_y.get(), -1,
pt_z.get());

pten::AddKernel<T, DeviceContext>(dev_ctx, src1, src2, -1, out);
}

template <typename DeviceContext, typename T>
void Tensor_Sub(const DeviceContext& dev_ctx, const framework::Tensor& src1,
const framework::Tensor& src2, framework::Tensor* out) {
out->Resize(src1.dims());
out->mutable_data<T>(dev_ctx.GetPlace());
auto pt_x = paddle::experimental::MakePtenDenseTensor(src1);
auto pt_y = paddle::experimental::MakePtenDenseTensor(src2);
auto pt_z = paddle::experimental::MakePtenDenseTensor(*out);
pten::SubtractKernel<T, DeviceContext>(dev_ctx, *pt_x.get(), *pt_y.get(), -1,
pt_z.get());

pten::SubtractKernel<T, DeviceContext>(dev_ctx, src1, src2, -1, out);
}

template <typename DeviceContext, typename T, size_t D>
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56 changes: 8 additions & 48 deletions paddle/fluid/operators/matmul_v2_op.h
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Expand Up @@ -52,13 +52,8 @@ class MatMulV2Kernel : public framework::OpKernel<T> {
auto& dev_ctx = ctx.device_context<DeviceContext>();
Out->mutable_data<T>(X->place());

auto pt_x = paddle::experimental::MakePtenDenseTensor(*X);
auto pt_y = paddle::experimental::MakePtenDenseTensor(*Y);
auto pt_out = paddle::experimental::MakePtenDenseTensor(*Out);

// call new kernel
pten::MatmulKernel<T>(dev_ctx, *pt_x, *pt_y, trans_x, trans_y,
pt_out.get());
pten::MatmulKernel<T>(dev_ctx, *X, *Y, trans_x, trans_y, Out);
}
};

Expand Down Expand Up @@ -151,19 +146,11 @@ class MatMulV2GradKernel : public framework::OpKernel<T> {
if (dx) dx->mutable_data<T>(ctx.GetPlace());
if (dy) dy->mutable_data<T>(ctx.GetPlace());

auto pt_x = paddle::experimental::MakePtenDenseTensor(*x);
auto pt_y = paddle::experimental::MakePtenDenseTensor(*y);
auto pt_dout = paddle::experimental::MakePtenDenseTensor(*dout);
auto pt_dx = dx ? paddle::experimental::MakePtenDenseTensor(*dx)
: std::unique_ptr<pten::DenseTensor>(nullptr);
auto pt_dy = dy ? paddle::experimental::MakePtenDenseTensor(*dy)
: std::unique_ptr<pten::DenseTensor>(nullptr);

auto& dev_ctx = ctx.device_context<DeviceContext>();

// call new kernel
pten::MatmulGradKernel<T>(dev_ctx, *pt_x, *pt_y, *pt_dout, transpose_x,
transpose_y, pt_dx.get(), pt_dy.get());
pten::MatmulGradKernel<T>(dev_ctx, *x, *y, *dout, transpose_x, transpose_y,
dx, dy);
}
};

Expand All @@ -188,21 +175,11 @@ class MatMulV2DoubleGradKernel : public framework::OpKernel<T> {
if (dy) dy->mutable_data<T>(context.GetPlace());
if (ddout) ddout->mutable_data<T>(context.GetPlace());

auto pt_x = paddle::experimental::MakePtenDenseTensor(*x);
auto pt_y = paddle::experimental::MakePtenDenseTensor(*y);
auto pt_dout = paddle::experimental::MakePtenDenseTensor(*dout);
auto pt_ddx = paddle::experimental::MakePtenDenseTensor(*ddx);
auto pt_ddy = paddle::experimental::MakePtenDenseTensor(*ddy);
auto pt_dx = paddle::experimental::MakePtenDenseTensor(*dx);
auto pt_dy = paddle::experimental::MakePtenDenseTensor(*dy);
auto pt_ddout = paddle::experimental::MakePtenDenseTensor(*ddout);

auto& dev_ctx = context.device_context<DeviceContext>();

// call new kernel
pten::MatmulDoubleGradKernel<T>(dev_ctx, *pt_x, *pt_y, *pt_dout, *pt_ddx,
*pt_ddy, transpose_x, transpose_y,
pt_dx.get(), pt_dy.get(), pt_ddout.get());
pten::MatmulDoubleGradKernel<T>(dev_ctx, *x, *y, *dout, *ddx, *ddy,
transpose_x, transpose_y, dx, dy, ddout);
}
};

Expand Down Expand Up @@ -238,28 +215,11 @@ class MatMulV2TripleGradKernel : public framework::OpKernel<T> {
if (out_d_ddx) out_d_ddx->mutable_data<T>(context.GetPlace());
if (out_d_ddy) out_d_ddy->mutable_data<T>(context.GetPlace());

auto pt_x = paddle::experimental::MakePtenDenseTensor(*x);
auto pt_y = paddle::experimental::MakePtenDenseTensor(*y);
auto pt_dout = paddle::experimental::MakePtenDenseTensor(*dout);
auto pt_ddx = paddle::experimental::MakePtenDenseTensor(*ddx);
auto pt_ddy = paddle::experimental::MakePtenDenseTensor(*ddy);
auto pt_d_dx = paddle::experimental::MakePtenDenseTensor(*d_dx);
auto pt_d_dy = paddle::experimental::MakePtenDenseTensor(*d_dy);
auto pt_d_ddout = paddle::experimental::MakePtenDenseTensor(*d_ddout);

auto pt_out_d_x = paddle::experimental::MakePtenDenseTensor(*out_d_x);
auto pt_out_d_y = paddle::experimental::MakePtenDenseTensor(*out_d_y);
auto pt_out_d_dout = paddle::experimental::MakePtenDenseTensor(*out_d_dout);
auto pt_out_d_ddx = paddle::experimental::MakePtenDenseTensor(*out_d_ddx);
auto pt_out_d_ddy = paddle::experimental::MakePtenDenseTensor(*out_d_ddy);

auto& dev_ctx = context.device_context<DeviceContext>();
// call new kernel
pten::MatmulTripleGradKernel<T>(dev_ctx, *pt_x, *pt_y, *pt_dout, *pt_ddx,
*pt_ddy, *pt_d_dx, *pt_d_dy, *pt_d_ddout,
transpose_x, transpose_y, pt_out_d_x.get(),
pt_out_d_y.get(), pt_out_d_dout.get(),
pt_out_d_ddx.get(), pt_out_d_ddy.get());
pten::MatmulTripleGradKernel<T>(
dev_ctx, *x, *y, *dout, *ddx, *ddy, *d_dx, *d_dy, *d_ddout, transpose_x,
transpose_y, out_d_x, out_d_y, out_d_dout, out_d_ddx, out_d_ddy);
}
};

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6 changes: 1 addition & 5 deletions paddle/fluid/operators/scale_op.h
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Expand Up @@ -65,12 +65,8 @@ class ScaleKernel : public framework::OpKernel<T> {
out->mutable_data<T>(in->place());
auto& dev_ctx = ctx.device_context<DeviceContext>();

auto pt_x = paddle::experimental::MakePtenDenseTensor(*in);
auto pt_out = paddle::experimental::MakePtenDenseTensor(*out);

// call new kernel
pten::ScaleKernel<T>(dev_ctx, *pt_x.get(), scale, bias, bias_after_scale,
pt_out.get());
pten::ScaleKernel<T>(dev_ctx, *in, scale, bias, bias_after_scale, out);
}
};

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5 changes: 1 addition & 4 deletions paddle/fluid/operators/sign_op.h
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Expand Up @@ -34,11 +34,8 @@ class SignKernel : public framework::OpKernel<T> {
auto& dev_ctx = context.device_context<DeviceContext>();
out->mutable_data<T>(x->place());

auto pt_x = paddle::experimental::MakePtenDenseTensor(*x);
auto pt_out = paddle::experimental::MakePtenDenseTensor(*out);

// call new kernel
pten::SignKernel<T, DeviceContext>(dev_ctx, *pt_x.get(), pt_out.get());
pten::SignKernel<T, DeviceContext>(dev_ctx, *x, out);
}
};

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