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#16153: Implement binary-ng fused input activations
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@patrickroberts
patrickroberts committed Dec 23, 2024
1 parent 5a5126d commit de965af
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Showing 17 changed files with 465 additions and 281 deletions.
6 changes: 3 additions & 3 deletions ttnn/cpp/ttnn/operations/eltwise/binary/common/binary_op_utils.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -149,11 +149,11 @@ std::map<std::string, std::string> get_defines(
defines["ELTWISE_OP"] = op_name.c_str();
defines["ELTWISE_OP_TYPE"] = op_binary_type.c_str();
if (fused_activations.has_value()) {
if (op_type == BinaryOpType::ADD and fused_activations.value().size() == 1 and
fused_activations.value().at(0).op_type == UnaryOpType::RELU) {
if (op_type == BinaryOpType::ADD and fused_activations->size() == 1 and
fused_activations->at(0).op_type == UnaryOpType::RELU and not input_tensor_a_activation.has_value()) {
defines["PACK_RELU"] = "1";
} else {
defines.merge(ttnn::operations::unary::utils::get_block_defines(fused_activations.value(), "0", idst));
defines.merge(ttnn::operations::unary::utils::get_block_defines(*fused_activations, "0", idst));
}
}

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93 changes: 71 additions & 22 deletions ttnn/cpp/ttnn/operations/eltwise/binary_ng/binary_ng.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -11,44 +11,93 @@ namespace ttnn::operations::binary_ng {
template <BinaryOpType binary_op_type>
Tensor BinaryNg<binary_op_type>::invoke(
uint8_t queue_id,
const Tensor &input_tensor_a,
const Tensor &input_tensor_b,
const std::optional<const DataType> &output_dtype,
const std::optional<MemoryConfig> &memory_config,
std::optional<Tensor> optional_output_tensor) {
const Tensor& input_tensor_a,
const Tensor& input_tensor_b,
const std::optional<const DataType>& output_dtype,
const std::optional<MemoryConfig>& memory_config,
std::optional<Tensor> optional_output_tensor,
tt::stl::Span<const ttnn::operations::unary::UnaryOpType> lhs_activations,
tt::stl::Span<const ttnn::operations::unary::UnaryOpType> rhs_activations,
tt::stl::Span<const ttnn::operations::unary::UnaryOpType> post_activations) {
return ttnn::prim::binary_ng(
queue_id, input_tensor_a, input_tensor_b, binary_op_type, output_dtype, memory_config, optional_output_tensor);
queue_id,
input_tensor_a,
input_tensor_b,
binary_op_type,
output_dtype,
memory_config,
optional_output_tensor,
lhs_activations,
rhs_activations,
post_activations);
}

template <BinaryOpType binary_op_type>
Tensor BinaryNg<binary_op_type>::invoke(
const Tensor &input_tensor_a,
const Tensor &input_tensor_b,
const std::optional<const DataType> &output_dtype,
const std::optional<MemoryConfig> &memory_config,
std::optional<Tensor> optional_output_tensor) {
return invoke(DefaultQueueId, input_tensor_a, input_tensor_b, output_dtype, memory_config, optional_output_tensor);
const Tensor& input_tensor_a,
const Tensor& input_tensor_b,
const std::optional<const DataType>& output_dtype,
const std::optional<MemoryConfig>& memory_config,
std::optional<Tensor> optional_output_tensor,
tt::stl::Span<const ttnn::operations::unary::UnaryOpType> lhs_activations,
tt::stl::Span<const ttnn::operations::unary::UnaryOpType> rhs_activations,
tt::stl::Span<const ttnn::operations::unary::UnaryOpType> post_activations) {
return invoke(
DefaultQueueId,
input_tensor_a,
input_tensor_b,
output_dtype,
memory_config,
optional_output_tensor,
lhs_activations,
rhs_activations,
post_activations);
}

template <BinaryOpType binary_op_type>
Tensor BinaryNg<binary_op_type>::invoke(
uint8_t queue_id,
const Tensor &input_tensor_a,
const Tensor& input_tensor_a,
float scalar,
const std::optional<const DataType> &output_dtype,
const std::optional<MemoryConfig> &memory_config,
std::optional<Tensor> optional_output_tensor) {
return ttnn::prim::binary_ng(queue_id, input_tensor_a, scalar, binary_op_type, output_dtype, memory_config, optional_output_tensor);
const std::optional<const DataType>& output_dtype,
const std::optional<MemoryConfig>& memory_config,
std::optional<Tensor> optional_output_tensor,
tt::stl::Span<const ttnn::operations::unary::UnaryOpType> lhs_activations,
tt::stl::Span<const ttnn::operations::unary::UnaryOpType> rhs_activations,
tt::stl::Span<const ttnn::operations::unary::UnaryOpType> post_activations) {
return ttnn::prim::binary_ng(
queue_id,
input_tensor_a,
scalar,
binary_op_type,
output_dtype,
memory_config,
optional_output_tensor,
lhs_activations,
rhs_activations,
post_activations);
}

template <BinaryOpType binary_op_type>
Tensor BinaryNg<binary_op_type>::invoke(
const Tensor &input_tensor_a,
const Tensor& input_tensor_a,
float scalar,
const std::optional<const DataType> &output_dtype,
const std::optional<MemoryConfig> &memory_config,
std::optional<Tensor> optional_output_tensor) {
return invoke(DefaultQueueId, input_tensor_a, scalar, output_dtype, memory_config, optional_output_tensor);
const std::optional<const DataType>& output_dtype,
const std::optional<MemoryConfig>& memory_config,
std::optional<Tensor> optional_output_tensor,
tt::stl::Span<const ttnn::operations::unary::UnaryOpType> lhs_activations,
tt::stl::Span<const ttnn::operations::unary::UnaryOpType> rhs_activations,
tt::stl::Span<const ttnn::operations::unary::UnaryOpType> post_activations) {
return invoke(
DefaultQueueId,
input_tensor_a,
scalar,
output_dtype,
memory_config,
optional_output_tensor,
lhs_activations,
rhs_activations,
post_activations);
}

template struct BinaryNg<BinaryOpType::ADD>;
Expand Down
52 changes: 33 additions & 19 deletions ttnn/cpp/ttnn/operations/eltwise/binary_ng/binary_ng.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -7,40 +7,53 @@

#include "ttnn/decorators.hpp"
#include "ttnn/operations/eltwise/binary_ng/types.hpp"
#include "ttnn/operations/eltwise/unary/common/unary_op_types.hpp"

namespace ttnn::operations::binary_ng {

template <BinaryOpType binary_op_type>
struct BinaryNg {
static Tensor invoke(
uint8_t queue_id,
const Tensor &input_tensor_a,
const Tensor &input_tensor_b,
const std::optional<const DataType> &output_dtype = std::nullopt,
const std::optional<MemoryConfig> &memory_config = std::nullopt,
std::optional<Tensor> optional_output_tensor = std::nullopt);
const Tensor& input_tensor_a,
const Tensor& input_tensor_b,
const std::optional<const DataType>& output_dtype = std::nullopt,
const std::optional<MemoryConfig>& memory_config = std::nullopt,
std::optional<Tensor> optional_output_tensor = std::nullopt,
tt::stl::Span<const unary::UnaryOpType> lhs_activations = {},
tt::stl::Span<const unary::UnaryOpType> rhs_activations = {},
tt::stl::Span<const unary::UnaryOpType> post_activations = {});

static Tensor invoke(
const Tensor &input_tensor_a,
const Tensor &input_tensor_b,
const std::optional<const DataType> &output_dtype = std::nullopt,
const std::optional<MemoryConfig> &memory_config = std::nullopt,
std::optional<Tensor> optional_output_tensor = std::nullopt);
const Tensor& input_tensor_a,
const Tensor& input_tensor_b,
const std::optional<const DataType>& output_dtype = std::nullopt,
const std::optional<MemoryConfig>& memory_config = std::nullopt,
std::optional<Tensor> optional_output_tensor = std::nullopt,
tt::stl::Span<const unary::UnaryOpType> lhs_activations = {},
tt::stl::Span<const unary::UnaryOpType> rhs_activations = {},
tt::stl::Span<const unary::UnaryOpType> post_activations = {});

static Tensor invoke(
uint8_t queue_id,
const Tensor &input_tensor_a,
const Tensor& input_tensor_a,
float scalar,
const std::optional<const DataType> &output_dtype = std::nullopt,
const std::optional<MemoryConfig> &memory_config = std::nullopt,
std::optional<Tensor> optional_output_tensor = std::nullopt);
const std::optional<const DataType>& output_dtype = std::nullopt,
const std::optional<MemoryConfig>& memory_config = std::nullopt,
std::optional<Tensor> optional_output_tensor = std::nullopt,
tt::stl::Span<const unary::UnaryOpType> lhs_activations = {},
tt::stl::Span<const unary::UnaryOpType> rhs_activations = {},
tt::stl::Span<const unary::UnaryOpType> post_activations = {});

static Tensor invoke(
const Tensor &input_tensor_a,
const Tensor& input_tensor_a,
float scalar,
const std::optional<const DataType> &output_dtype = std::nullopt,
const std::optional<MemoryConfig> &memory_config = std::nullopt,
std::optional<Tensor> optional_output_tensor = std::nullopt);
const std::optional<const DataType>& output_dtype = std::nullopt,
const std::optional<MemoryConfig>& memory_config = std::nullopt,
std::optional<Tensor> optional_output_tensor = std::nullopt,
tt::stl::Span<const unary::UnaryOpType> lhs_activations = {},
tt::stl::Span<const unary::UnaryOpType> rhs_activations = {},
tt::stl::Span<const unary::UnaryOpType> post_activations = {});
};

} // namespace ttnn::operations::binary_ng
Expand Down Expand Up @@ -117,4 +130,5 @@ constexpr auto logaddexp = ttnn::register_operation_with_auto_launch_op<
constexpr auto logaddexp2 = ttnn::register_operation_with_auto_launch_op<
"ttnn::experimental::logaddexp2",
ttnn::operations::binary_ng::BinaryNg<operations::binary_ng::BinaryOpType::LOGADDEXP2>>();
}

} // namespace ttnn::experimental
36 changes: 33 additions & 3 deletions ttnn/cpp/ttnn/operations/eltwise/binary_ng/binary_ng_pybind.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -24,15 +24,30 @@ void bind_binary_ng_operation(py::module& module, T op, const std::string& docst
const std::optional<const DataType>& dtype,
const std::optional<ttnn::MemoryConfig>& memory_config,
const std::optional<ttnn::Tensor>& output_tensor,
const ttnn::SmallVector<unary::UnaryOpType>& lhs_activations,
const ttnn::SmallVector<unary::UnaryOpType>& rhs_activations,
const ttnn::SmallVector<unary::UnaryOpType>& post_activations,
const uint8_t& queue_id) -> ttnn::Tensor {
return self(queue_id, input_tensor_a, scalar, dtype, memory_config, output_tensor);
return self(
queue_id,
input_tensor_a,
scalar,
dtype,
memory_config,
output_tensor,
lhs_activations,
rhs_activations,
post_activations);
},
py::arg("input_tensor_a"),
py::arg("scalar"),
py::kw_only(),
py::arg("dtype") = std::nullopt,
py::arg("memory_config") = std::nullopt,
py::arg("output_tensor") = std::nullopt,
py::arg("lhs_activations") = ttnn::SmallVector<unary::UnaryOpType>(),
py::arg("rhs_activations") = ttnn::SmallVector<unary::UnaryOpType>(),
py::arg("post_activations") = ttnn::SmallVector<unary::UnaryOpType>(),
py::arg("queue_id") = 0},

// tensor and tensor
Expand All @@ -43,15 +58,30 @@ void bind_binary_ng_operation(py::module& module, T op, const std::string& docst
const std::optional<const DataType>& dtype,
const std::optional<ttnn::MemoryConfig>& memory_config,
const std::optional<ttnn::Tensor>& output_tensor,
const ttnn::SmallVector<unary::UnaryOpType>& lhs_activations,
const ttnn::SmallVector<unary::UnaryOpType>& rhs_activations,
const ttnn::SmallVector<unary::UnaryOpType>& post_activations,
uint8_t queue_id) -> ttnn::Tensor {
return self(queue_id, input_tensor_a, input_tensor_b, dtype, memory_config, output_tensor);
return self(
queue_id,
input_tensor_a,
input_tensor_b,
dtype,
memory_config,
output_tensor,
lhs_activations,
rhs_activations,
post_activations);
},
py::arg("input_tensor_a"),
py::arg("input_tensor_b"),
py::kw_only(),
py::arg("dtype") = std::nullopt,
py::arg("memory_config") = std::nullopt,
py::arg("output_tensor") = std::nullopt,
py::arg("lhs_activations") = ttnn::SmallVector<unary::UnaryOpType>(),
py::arg("rhs_activations") = ttnn::SmallVector<unary::UnaryOpType>(),
py::arg("post_activations") = ttnn::SmallVector<unary::UnaryOpType>(),
py::arg("queue_id") = 0});
}
} // namespace detail
Expand All @@ -77,4 +107,4 @@ void py_module(py::module& module) {
detail::bind_binary_ng_operation(module, ttnn::experimental::logaddexp, "Binary Logaddexp Operation");
detail::bind_binary_ng_operation(module, ttnn::experimental::logaddexp2, "Binary Logaddexp2 Operation");
}
} // namespace ttnn::operations::eltwise::binary_ng
} // namespace ttnn::operations::binary_ng
25 changes: 22 additions & 3 deletions ttnn/cpp/ttnn/operations/eltwise/binary_ng/device/binary_ng_device_operation.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -40,7 +40,14 @@ SubtileBroadcastType get_subtile_broadcast_type(uint32_t a_h, uint32_t a_w, uint

tt::stl::hash::hash_t BinaryNgDeviceOperation::operation_attributes_t::to_hash() const {
return tt::stl::hash::hash_objects_with_default_seed(
binary_op_type, memory_config, get_dtype(), compute_kernel_config, subtile_broadcast_type);
binary_op_type,
lhs_activations,
rhs_activations,
post_activations,
memory_config,
get_dtype(),
compute_kernel_config,
subtile_broadcast_type);
}

DataType BinaryNgDeviceOperation::operation_attributes_t::get_dtype() const {
Expand Down Expand Up @@ -197,7 +204,10 @@ BinaryNgDeviceOperation::invoke(
BinaryOpType binary_op_type,
const std::optional<const DataType>& output_dtype,
const std::optional<MemoryConfig>& memory_config,
std::optional<Tensor> optional_output_tensor) {
std::optional<Tensor> optional_output_tensor,
tt::stl::Span<const ttnn::operations::unary::UnaryOpType> lhs_activations,
tt::stl::Span<const ttnn::operations::unary::UnaryOpType> rhs_activations,
tt::stl::Span<const ttnn::operations::unary::UnaryOpType> post_activations) {
auto subtile_broadcast_type = get_subtile_broadcast_type(
input_tensor_a_arg.get_logical_shape()[-2],
input_tensor_a_arg.get_logical_shape()[-1],
Expand All @@ -207,6 +217,9 @@ BinaryNgDeviceOperation::invoke(
return {
operation_attributes_t{
binary_op_type,
{lhs_activations.begin(), lhs_activations.end()},
{rhs_activations.begin(), rhs_activations.end()},
{post_activations.begin(), post_activations.end()},
std::nullopt,
memory_config.value_or(input_tensor_a_arg.memory_config()),
input_tensor_a_arg.get_dtype(),
Expand All @@ -223,10 +236,16 @@ BinaryNgDeviceOperation::invoke(
BinaryOpType binary_op_type,
const std::optional<const DataType>& output_dtype,
const std::optional<MemoryConfig>& memory_config,
std::optional<Tensor> optional_output_tensor) {
std::optional<Tensor> optional_output_tensor,
tt::stl::Span<const unary::UnaryOpType> lhs_activations,
tt::stl::Span<const unary::UnaryOpType> rhs_activations,
tt::stl::Span<const unary::UnaryOpType> post_activations) {
return {
operation_attributes_t{
binary_op_type,
{lhs_activations.begin(), lhs_activations.end()},
{rhs_activations.begin(), rhs_activations.end()},
{post_activations.begin(), post_activations.end()},
scalar,
memory_config.value_or(input_tensor_a_arg.memory_config()),
input_tensor_a_arg.get_dtype(),
Expand Down
15 changes: 12 additions & 3 deletions ttnn/cpp/ttnn/operations/eltwise/binary_ng/device/binary_ng_device_operation.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@
#include "ttnn/device_operation.hpp"
#include "ttnn/operations/core/compute_kernel/compute_kernel_config.hpp"
#include "ttnn/operations/eltwise/binary_ng/types.hpp"

#include "ttnn/operations/eltwise/unary/common/unary_op_types.hpp"
namespace ttnn::operations::binary_ng {

enum class SubtileBroadcastType {
Expand All @@ -31,6 +31,9 @@ struct BinaryNgDeviceOperation {

struct operation_attributes_t {
BinaryOpType binary_op_type;
ttnn::SmallVector<unary::UnaryOpType> lhs_activations;
ttnn::SmallVector<unary::UnaryOpType> rhs_activations;
ttnn::SmallVector<unary::UnaryOpType> post_activations;
std::optional<float> scalar;
MemoryConfig memory_config;
DataType input_dtype;
Expand Down Expand Up @@ -86,7 +89,10 @@ struct BinaryNgDeviceOperation {
BinaryOpType binary_op_type,
const std::optional<const DataType>& output_dtype,
const std::optional<MemoryConfig>& memory_config,
std::optional<Tensor> optional_output_tensor);
std::optional<Tensor> optional_output_tensor,
tt::stl::Span<const unary::UnaryOpType> lhs_activations,
tt::stl::Span<const unary::UnaryOpType> rhs_activations,
tt::stl::Span<const unary::UnaryOpType> post_activations);

// tensor-scalar invocation
static std::tuple<operation_attributes_t, tensor_args_t> invoke(
Expand All @@ -95,7 +101,10 @@ struct BinaryNgDeviceOperation {
BinaryOpType binary_op_type,
const std::optional<const DataType>& output_dtype,
const std::optional<MemoryConfig>& memory_config,
std::optional<Tensor> optional_output_tensor);
std::optional<Tensor> optional_output_tensor,
tt::stl::Span<const unary::UnaryOpType> lhs_activations,
tt::stl::Span<const unary::UnaryOpType> rhs_activations,
tt::stl::Span<const unary::UnaryOpType> post_activations);
};

} // namespace ttnn::operations::binary_ng
Expand Down
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