Commit 375c7b8d authored by turneram's avatar turneram
Browse files

Remove layernorm operator

parent 276dda76
......@@ -117,7 +117,6 @@ register_migraphx_ops(
if_op
im2col
isnan
layernorm
leaky_relu
less
load
......
#ifndef MIGRAPHX_GUARD_OPERATORS_LAYERNORMALIZATION_HPP
#define MIGRAPHX_GUARD_OPERATORS_LAYERNORMALIZATION_HPP
#include <array>
#include <migraphx/check_shapes.hpp>
#include <migraphx/stringutils.hpp>
#include <migraphx/streamutils.hpp>
#include <migraphx/literal.hpp>
#include <migraphx/shape_for_each.hpp>
#include <migraphx/config.hpp>
#include <migraphx/value.hpp>
#include <migraphx/op/normalize_attribute.hpp>
#include <migraphx/par_for.hpp>
#include <cmath>
#include <utility>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace op {
struct layernorm
{
float epsilon = 1e-3;
int64_t axis = -1;
template <class Self, class F>
static auto reflect(Self& self, F f)
{
return pack(f(self.epsilon, "epsilon"), f(self.axis, "axis"));
}
value attributes() const
{
value normalize;
normalize["axis"] = value::array{normalize_attribute::include_min};
return {{"normalize_axes", normalize}};
}
std::string name() const { return "layernorm"; }
shape normalize_compute_shape(std::vector<shape> inputs) const
{
if(inputs.size() == 2)
{
if(inputs.at(1).lens().front() != inputs.front().lens().at(axis))
MIGRAPHX_THROW("LAYERNORM: weights have wrong shape");
}
if(inputs.size() == 3)
{
if(inputs.at(2).lens().front() != inputs.front().lens().at(axis))
MIGRAPHX_THROW("LAYERNORM: bias has wrong shape");
}
return inputs.front();
}
argument compute(const shape& output_shape, std::vector<argument> args) const
{
argument result{output_shape};
auto x_lens = args.front().get_shape().lens();
auto norm_count = std::accumulate(
x_lens.begin(), x_lens.begin() + axis, std::size_t{1}, std::multiplies<std::size_t>());
auto norm_size = std::accumulate(
x_lens.begin() + axis, x_lens.end(), std::size_t{1}, std::multiplies<std::size_t>());
if(args.size() == 3)
{
visit_all(result, args[0], args[1], args[2])(
[&](auto output, auto data, auto weights, auto bias) {
par_for(norm_count, [&](auto idx) {
auto offset = idx * norm_size;
double mean = 0;
double mean_square = 0;
for(std::size_t i = 0; i < norm_size; ++i)
{
mean += data[offset + i];
mean_square += data[offset + i] * data[offset + i];
}
mean /= norm_size;
mean_square = sqrt(mean_square / norm_size - mean * mean + epsilon);
for(std::size_t i = 0; i < norm_size; ++i)
{
if(args.size() == 3)
output[offset + i] =
(data[offset + i] - mean) / mean_square * weights[i] + bias[i];
else
output[offset + i] =
(data[offset + i] - mean) / mean_square * weights[i];
}
});
});
}
else
{
visit_all(result, args[0])([&](auto output, auto data) {
par_for(norm_count, [&](auto idx) {
auto offset = idx * norm_size;
double mean = 0;
double mean_square = 0;
for(std::size_t i = 0; i < norm_size; ++i)
{
mean += data[offset + i];
mean_square += data[offset + i] * data[offset + i];
}
mean /= norm_size;
mean_square = sqrt(mean_square / norm_size - mean * mean + epsilon);
for(std::size_t i = 0; i < norm_size; ++i)
{
output[offset + i] = (data[offset + i] - mean) / mean_square;
// scale and bias handled by pointwise ops
}
});
});
}
return result;
}
};
} // namespace op
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
#endif
......@@ -43,7 +43,6 @@
#include <migraphx/op/if_op.hpp>
#include <migraphx/op/im2col.hpp>
#include <migraphx/op/isnan.hpp>
#include <migraphx/op/layernorm.hpp>
#include <migraphx/op/leaky_relu.hpp>
#include <migraphx/op/less.hpp>
#include <migraphx/op/load.hpp>
......
#include <migraphx/onnx/op_parser.hpp>
#include <migraphx/ranges.hpp>
#include <migraphx/make_op.hpp>
#include <migraphx/op/layernorm.hpp>
#include <migraphx/argument.hpp>
#include <migraphx/instruction.hpp>
......
......@@ -148,7 +148,6 @@ add_library(migraphx_gpu
int8_conv_pack.cpp
int8_gemm_pack.cpp
kernel.cpp
layernorm.cpp
lowering.cpp
logsoftmax.cpp
loop.cpp
......@@ -205,7 +204,6 @@ register_migraphx_gpu_ops(hip_
floor
gather
greater
layernorm
less
log
logsoftmax
......
#ifndef MIGRAPHX_GUARD_RTGLIB_DEVICE_LAYERNORM_HPP
#define MIGRAPHX_GUARD_RTGLIB_DEVICE_LAYERNORM_HPP
#include <migraphx/argument.hpp>
#include <migraphx/config.hpp>
#include <hip/hip_runtime_api.h>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace gpu {
namespace device {
void layernorm(hipStream_t stream, const argument& result, const argument& arg1);
void triadd_layernorm(hipStream_t stream,
const argument& result,
const argument& arg1,
const argument& arg2,
const argument& arg3);
} // namespace device
} // namespace gpu
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
#endif
#ifndef MIGRAPHX_GUARD_RTGLIB_LAYERNORM_HPP
#define MIGRAPHX_GUARD_RTGLIB_LAYERNORM_HPP
#include <migraphx/op/layernorm.hpp>
#include <migraphx/shape.hpp>
#include <migraphx/reflect.hpp>
#include <migraphx/argument.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace gpu {
struct context;
struct hip_layernorm
{
op::layernorm op;
template <class Self, class F>
static auto reflect(Self& self, F f)
{
return migraphx::reflect(self.op, f);
}
std::string name() const { return "gpu::layernorm"; }
shape compute_shape(std::vector<shape> inputs) const;
argument
compute(context& ctx, const shape& output_shape, const std::vector<argument>& args) const;
void finalize(context&, const shape&, const std::vector<shape>&);
std::ptrdiff_t output_alias(const std::vector<shape>& shapes) const
{
return shapes.size() - 1;
}
};
} // namespace gpu
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
#endif
#include <migraphx/gpu/layernorm.hpp>
#include <migraphx/gpu/context.hpp>
#include <migraphx/gpu/device/layernorm.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace gpu {
shape hip_layernorm::compute_shape(std::vector<shape> inputs) const
{
inputs.pop_back();
return op.normalize_compute_shape(inputs);
}
argument hip_layernorm::compute(context& ctx, const shape&, const std::vector<argument>& args) const
{
device::layernorm(ctx.get_stream().get(), args.back(), args[0]);
return args.back();
}
} // namespace gpu
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
......@@ -11,7 +11,6 @@
#include <migraphx/op/dot.hpp>
#include <migraphx/op/elu.hpp>
#include <migraphx/op/if_op.hpp>
#include <migraphx/op/layernorm.hpp>
#include <migraphx/op/leaky_relu.hpp>
#include <migraphx/op/lrn.hpp>
#include <migraphx/op/pooling.hpp>
......
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