@@ -122,7 +122,7 @@ Status ShapeInferenceState::AwaitShapesReady(const GraphExecutionContext &contex | |||||
GE_CHECK_NOTNULL(input_desc); | GE_CHECK_NOTNULL(input_desc); | ||||
int64_t tensor_size = -1; | int64_t tensor_size = -1; | ||||
(void) TensorUtils::GetSize(*src_tensor_desc, tensor_size); | (void) TensorUtils::GetSize(*src_tensor_desc, tensor_size); | ||||
GELOGD("[%s] Update input shape [%u] with shape: [%s] and ori_shape: [%s]", | |||||
GELOGD("[%s] Update input shape [%u] with shape: [%s] and ori_shape: [%s], index = %zu", | |||||
node_item.NodeName().c_str(), | node_item.NodeName().c_str(), | ||||
idx, | idx, | ||||
src_tensor_desc->GetShape().ToString().c_str(), | src_tensor_desc->GetShape().ToString().c_str(), | ||||
@@ -71,7 +71,7 @@ Status ShapeInferenceEngine::InferShape(NodeState &node_state) { | |||||
std::lock_guard<std::mutex> lk(mu_); | std::lock_guard<std::mutex> lk(mu_); | ||||
RECORD_SHAPE_INFERENCE_EVENT(execution_context_, node_item.NodeName().c_str(), "[InferShapeAndType] Start"); | RECORD_SHAPE_INFERENCE_EVENT(execution_context_, node_item.NodeName().c_str(), "[InferShapeAndType] Start"); | ||||
GE_CHK_STATUS_RET(ShapeRefiner::InferShapeAndTypeForRunning(node_item.node, true), | GE_CHK_STATUS_RET(ShapeRefiner::InferShapeAndTypeForRunning(node_item.node, true), | ||||
"Invoke InferShapeAndType failed."); | |||||
"Invoke InferShapeAndType failed."); | |||||
RECORD_SHAPE_INFERENCE_EVENT(execution_context_, node_item.NodeName().c_str(), "[InferShapeAndType] End"); | RECORD_SHAPE_INFERENCE_EVENT(execution_context_, node_item.NodeName().c_str(), "[InferShapeAndType] End"); | ||||
} | } | ||||
@@ -229,66 +229,87 @@ Status ShapeInferenceEngine::UpdatePeerNodeShape(const Node &node) { | |||||
return SUCCESS; | return SUCCESS; | ||||
} | } | ||||
Status ShapeInferenceEngine::CanonicalizeShape(GeTensorDesc &tensor_desc, | |||||
std::vector<int64_t> &shape, | |||||
bool fallback_with_range) { | |||||
const auto &tensor_shape = tensor_desc.MutableShape(); | |||||
if (tensor_shape.IsUnknownShape()) { | |||||
if (!fallback_with_range) { | |||||
GELOGE(INTERNAL_ERROR, "Output shape is still unknown after shape inference. shape = [%s]", | |||||
tensor_shape.ToString().c_str()); | |||||
return INTERNAL_ERROR; | |||||
} | |||||
GELOGD("Calc output size by range"); | |||||
std::vector<std::pair<int64_t, int64_t>> shape_range; | |||||
GE_CHK_GRAPH_STATUS_RET(tensor_desc.GetShapeRange(shape_range), "Failed to get shape range"); | |||||
if (shape_range.size() != shape.size()) { | |||||
GELOGE(INTERNAL_ERROR, "Number of shape ranges (%zu) mismatches that of dims (%zu)", | |||||
shape_range.size(), | |||||
shape.size()); | |||||
return INTERNAL_ERROR; | |||||
} | |||||
for (size_t dim_index = 0; dim_index < shape.size(); ++dim_index) { | |||||
if (shape[dim_index] == ge::UNKNOWN_DIM) { | |||||
shape[dim_index] = shape_range[dim_index].second; | |||||
} | |||||
} | |||||
GELOGD("After canonicalization, shape = [%s], before = [%s]", | |||||
GeShape(shape).ToString().c_str(), | |||||
tensor_shape.ToString().c_str()); | |||||
} | |||||
return SUCCESS; | |||||
} | |||||
Status ShapeInferenceEngine::CalcTensorSize(DataType data_type, | |||||
const std::vector<int64_t> &shape, | |||||
int64_t &tensor_size) { | |||||
GELOGD("To calc tensor size by shape = [%s]", GeShape(shape).ToString().c_str()); | |||||
uint32_t type_size; | |||||
if (!TypeUtils::GetDataTypeLength(data_type, type_size)) { | |||||
GELOGE(INTERNAL_ERROR, "Failed to get data type size"); | |||||
return INTERNAL_ERROR; | |||||
} | |||||
tensor_size = type_size; | |||||
for (const auto &dim : shape) { | |||||
GE_CHECK_GE(dim, 0); | |||||
GE_CHK_STATUS_RET(Int64MulCheckOverflow(tensor_size, dim), | |||||
"Shape size overflow, shape = [%s]", | |||||
GeShape(shape).ToString().c_str()); | |||||
tensor_size *= dim; | |||||
} | |||||
GE_CHK_STATUS_RET(CheckInt64AddOverflow(tensor_size, kAlignment - 1), | |||||
"Tensor size is too large: %ld, shape = [%s]", | |||||
tensor_size, | |||||
GeShape(shape).ToString().c_str()); | |||||
tensor_size = (tensor_size + kAlignment - 1) / kAlignment * kAlignment; | |||||
return SUCCESS; | |||||
} | |||||
Status ShapeInferenceEngine::CalcOutputTensorSizes(const NodeItem &node_item, bool fallback_with_range) { | Status ShapeInferenceEngine::CalcOutputTensorSizes(const NodeItem &node_item, bool fallback_with_range) { | ||||
auto op_desc = node_item.GetOpDesc(); | auto op_desc = node_item.GetOpDesc(); | ||||
for (size_t output_index = 0; output_index < op_desc->GetOutputsSize(); ++output_index) { | for (size_t output_index = 0; output_index < op_desc->GetOutputsSize(); ++output_index) { | ||||
auto tensor_desc = op_desc->MutableOutputDesc(output_index); | auto tensor_desc = op_desc->MutableOutputDesc(output_index); | ||||
GE_CHECK_NOTNULL(tensor_desc); | GE_CHECK_NOTNULL(tensor_desc); | ||||
const auto &shape = tensor_desc->MutableShape(); | const auto &shape = tensor_desc->MutableShape(); | ||||
// modify on copy | |||||
auto dims = shape.GetDims(); | auto dims = shape.GetDims(); | ||||
auto dim_num = dims.size(); | |||||
if (shape.IsUnknownShape()) { | |||||
if (!fallback_with_range) { | |||||
GELOGE(INTERNAL_ERROR, "[%s] Shape of output[%zu] is still unknown after shape inference. shape = [%s]", | |||||
node_item.NodeName().c_str(), | |||||
output_index, | |||||
shape.ToString().c_str()); | |||||
return INTERNAL_ERROR; | |||||
} | |||||
GELOGD("[%s] Calc output[%zu] size by range", node_item.NodeName().c_str(), output_index); | |||||
std::vector<std::pair<int64_t, int64_t>> shape_range; | |||||
GE_CHK_GRAPH_STATUS_RET(tensor_desc->GetShapeRange(shape_range), | |||||
"[$s] Failed to get shape range for output: %zu", | |||||
node_item.NodeName().c_str(), | |||||
output_index); | |||||
if (shape_range.size() != dim_num) { | |||||
GELOGE(INTERNAL_ERROR, "[%s] Number of shape ranges (%zu) mismatches that of dims (%zu), index = %zu", | |||||
node_item.NodeName().c_str(), | |||||
shape_range.size(), | |||||
dim_num, | |||||
output_index); | |||||
return INTERNAL_ERROR; | |||||
} | |||||
for (size_t dim_index = 0; dim_index < dim_num; ++dim_index) { | |||||
if (dims[dim_index] == ge::UNKNOWN_DIM) { | |||||
dims[dim_index] = shape_range[dim_index].second; | |||||
} | |||||
} | |||||
} | |||||
uint32_t type_size = 0; | |||||
if (!TypeUtils::GetDataTypeLength(tensor_desc->GetDataType(), type_size)) { | |||||
GELOGE(INTERNAL_ERROR, "Failed to get data type size"); | |||||
return INTERNAL_ERROR; | |||||
} | |||||
int64_t tensor_size = type_size; | |||||
for (const auto &dim : dims) { | |||||
GE_CHECK_GE(dim, 0); | |||||
GE_CHK_STATUS_RET(Int64MulCheckOverflow(tensor_size, dim), | |||||
"[%s] Shape size overflow, shape = [%s]", | |||||
node_item.NodeName().c_str(), | |||||
shape.ToString().c_str()); | |||||
tensor_size *= dim; | |||||
} | |||||
GE_CHK_STATUS_RET(CanonicalizeShape(*tensor_desc, dims, fallback_with_range), | |||||
"[%s] Failed to canonicalize shape for output %zu", | |||||
node_item.NodeName().c_str(), | |||||
output_index); | |||||
GE_CHK_STATUS_RET(CheckInt64AddOverflow(tensor_size, kAlignment - 1), | |||||
"[%s] Output[%zu] Tensor size too large, shape = [%s]", | |||||
int64_t tensor_size; | |||||
GE_CHK_STATUS_RET(CalcTensorSize(tensor_desc->GetDataType(), dims, tensor_size), | |||||
"[%s] Failed to calc tensor size for output %zu", | |||||
node_item.NodeName().c_str(), | node_item.NodeName().c_str(), | ||||
output_index, | |||||
shape.ToString().c_str()); | |||||
tensor_size = (tensor_size + kAlignment - 1) / kAlignment * kAlignment; | |||||
output_index); | |||||
GELOGD("[%s] Tensor size of output %zu = %ld", node_item.NodeName().c_str(), output_index, tensor_size); | |||||
(void) TensorUtils::SetSize(*tensor_desc, tensor_size); | (void) TensorUtils::SetSize(*tensor_desc, tensor_size); | ||||
} | } | ||||
@@ -37,6 +37,8 @@ class ShapeInferenceEngine { | |||||
static Status CalcOutputTensorSizes(const NodeItem &node_item, bool fallback_with_range = false); | static Status CalcOutputTensorSizes(const NodeItem &node_item, bool fallback_with_range = false); | ||||
private: | private: | ||||
static Status CanonicalizeShape(GeTensorDesc &tensor_desc, std::vector<int64_t> &shape, bool fallback_with_range); | |||||
static Status CalcTensorSize(DataType data_type, const std::vector<int64_t> &shape, int64_t &tensor_size); | |||||
static Status UpdatePeerNodeShape(const Node &node); | static Status UpdatePeerNodeShape(const Node &node); | ||||
Status AwaitDependentNodes(NodeState &node_state); | Status AwaitDependentNodes(NodeState &node_state); | ||||
@@ -127,12 +127,7 @@ Status NodeItem::Create(const NodePtr &node, std::unique_ptr<NodeItem> &node_ite | |||||
return SUCCESS; | return SUCCESS; | ||||
} | } | ||||
Status NodeItem::Init() { | |||||
GE_CHECK_LE(op_desc->GetInputsSize(), INT32_MAX); | |||||
GE_CHECK_LE(op_desc->GetOutputsSize(), INT32_MAX); | |||||
num_inputs = static_cast<int>(op_desc->GetInputsSize()); | |||||
num_outputs = static_cast<int>(op_desc->GetOutputsSize()); | |||||
void NodeItem::ResolveOptionalInputs() { | |||||
if (op_desc->GetAllInputsSize() != op_desc->GetInputsSize()) { | if (op_desc->GetAllInputsSize() != op_desc->GetInputsSize()) { | ||||
has_optional_inputs = true; | has_optional_inputs = true; | ||||
for (size_t i = 0; i < op_desc->GetAllInputsSize(); ++i) { | for (size_t i = 0; i < op_desc->GetAllInputsSize(); ++i) { | ||||
@@ -144,7 +139,18 @@ Status NodeItem::Init() { | |||||
} | } | ||||
} | } | ||||
} | } | ||||
} | |||||
Status NodeItem::InitInputsAndOutputs() { | |||||
GE_CHECK_LE(op_desc->GetInputsSize(), INT32_MAX); | |||||
GE_CHECK_LE(op_desc->GetOutputsSize(), INT32_MAX); | |||||
num_inputs = static_cast<int>(op_desc->GetInputsSize()); | |||||
num_outputs = static_cast<int>(op_desc->GetOutputsSize()); | |||||
ResolveOptionalInputs(); | |||||
return SUCCESS; | |||||
} | |||||
Status NodeItem::ResolveDynamicState() { | |||||
(void) AttrUtils::GetBool(op_desc, ATTR_NAME_FORCE_UNKNOWN_SHAPE, is_dynamic); | (void) AttrUtils::GetBool(op_desc, ATTR_NAME_FORCE_UNKNOWN_SHAPE, is_dynamic); | ||||
GELOGD("node name = %s, is_dynamic = %d.", this->node_name.c_str(), is_dynamic); | GELOGD("node name = %s, is_dynamic = %d.", this->node_name.c_str(), is_dynamic); | ||||
if (!is_dynamic) { | if (!is_dynamic) { | ||||
@@ -152,42 +158,54 @@ Status NodeItem::Init() { | |||||
"[%s] Failed to get shape status.", | "[%s] Failed to get shape status.", | ||||
node->GetName().c_str()); | node->GetName().c_str()); | ||||
} | } | ||||
return SUCCESS; | |||||
} | |||||
if (is_dynamic) { | |||||
for (int i = 0; i < num_inputs; ++i) { | |||||
const auto &input_desc = MutableInputDesc(i); | |||||
GE_CHECK_NOTNULL(input_desc); | |||||
if (input_desc->MutableShape().IsUnknownShape()) { | |||||
is_input_shape_static_.push_back(false); | |||||
} else { | |||||
num_static_input_shapes++; | |||||
is_input_shape_static_.push_back(true); | |||||
GELOGD("[%s] The shape of input[%d] is static. shape = [%s]", | |||||
NodeName().c_str(), i, input_desc->MutableShape().ToString().c_str()); | |||||
} | |||||
Status NodeItem::ResolveStaticInputsAndOutputs() { | |||||
for (int i = 0; i < num_inputs; ++i) { | |||||
const auto &input_desc = MutableInputDesc(i); | |||||
GE_CHECK_NOTNULL(input_desc); | |||||
if (input_desc->MutableShape().IsUnknownShape()) { | |||||
is_input_shape_static_.push_back(false); | |||||
} else { | |||||
num_static_input_shapes++; | |||||
is_input_shape_static_.push_back(true); | |||||
GELOGD("[%s] The shape of input[%d] is static. shape = [%s]", | |||||
NodeName().c_str(), i, input_desc->MutableShape().ToString().c_str()); | |||||
} | } | ||||
} | |||||
for (int i = 0; i < num_outputs; ++i) { | |||||
const auto &output_desc = op_desc->MutableOutputDesc(i); | |||||
GE_CHECK_NOTNULL(output_desc); | |||||
if (output_desc->MutableShape().IsUnknownShape()) { | |||||
is_output_shape_static = false; | |||||
break; | |||||
} | |||||
for (int i = 0; i < num_outputs; ++i) { | |||||
const auto &output_desc = op_desc->MutableOutputDesc(i); | |||||
GE_CHECK_NOTNULL(output_desc); | |||||
if (output_desc->MutableShape().IsUnknownShape()) { | |||||
is_output_shape_static = false; | |||||
break; | |||||
} | } | ||||
} | |||||
if (is_output_shape_static) { | |||||
GE_CHK_STATUS_RET_NOLOG(ShapeInferenceEngine::CalcOutputTensorSizes(*this)); | |||||
} | |||||
if (is_output_shape_static) { | |||||
GE_CHK_STATUS_RET_NOLOG(ShapeInferenceEngine::CalcOutputTensorSizes(*this)); | |||||
} | |||||
return SUCCESS; | |||||
} | |||||
if (IsControlOp() || node_type == PARTITIONEDCALL) { | |||||
shape_inference_type = DEPEND_COMPUTE; | |||||
} else { | |||||
int32_t unknown_shape_type_val = 0; | |||||
(void) AttrUtils::GetInt(op_desc, ::ge::ATTR_NAME_UNKNOWN_SHAPE_TYPE, unknown_shape_type_val); | |||||
shape_inference_type = static_cast<UnknowShapeOpType>(unknown_shape_type_val); | |||||
} | |||||
void NodeItem::ResolveUnknownShapeType() { | |||||
if (IsControlOp() || node_type == PARTITIONEDCALL) { | |||||
shape_inference_type = DEPEND_COMPUTE; | |||||
} else { | |||||
int32_t unknown_shape_type_val = 0; | |||||
(void) AttrUtils::GetInt(op_desc, ::ge::ATTR_NAME_UNKNOWN_SHAPE_TYPE, unknown_shape_type_val); | |||||
shape_inference_type = static_cast<UnknowShapeOpType>(unknown_shape_type_val); | |||||
} | |||||
} | |||||
Status NodeItem::Init() { | |||||
GE_CHK_STATUS_RET_NOLOG(InitInputsAndOutputs()); | |||||
GE_CHK_STATUS_RET_NOLOG(ResolveDynamicState()); | |||||
if (is_dynamic) { | |||||
ResolveUnknownShapeType(); | |||||
GE_CHK_STATUS_RET_NOLOG(ResolveStaticInputsAndOutputs()); | |||||
GE_CHK_STATUS_RET(ParseFusedSubgraph(*this), "[%s] Failed to parse fused subgraph", node_name.c_str()); | GE_CHK_STATUS_RET(ParseFusedSubgraph(*this), "[%s] Failed to parse fused subgraph", node_name.c_str()); | ||||
} | } | ||||
@@ -103,6 +103,11 @@ struct NodeItem { | |||||
private: | private: | ||||
explicit NodeItem(NodePtr node); | explicit NodeItem(NodePtr node); | ||||
Status Init(); | Status Init(); | ||||
Status InitInputsAndOutputs(); | |||||
void ResolveOptionalInputs(); | |||||
Status ResolveDynamicState(); | |||||
Status ResolveStaticInputsAndOutputs(); | |||||
void ResolveUnknownShapeType(); | |||||
std::vector<bool> is_input_shape_static_; | std::vector<bool> is_input_shape_static_; | ||||
std::vector<uint32_t> input_desc_indices_; | std::vector<uint32_t> input_desc_indices_; | ||||