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chore: Rebase with master
Signed-off-by: Dheeraj Peri <[email protected]>
2 parents 5c26000 + 4839b11 commit 780fd4f

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7 files changed

+386
-120
lines changed

7 files changed

+386
-120
lines changed

‎core/conversion/conversion.cpp

Lines changed: 19 additions & 8 deletions
Original file line numberDiff line numberDiff line change
@@ -105,7 +105,8 @@ void AddLayer(ConversionCtx* ctx, const torch::jit::Node* n) {
105105
// Node input has not been converted yet or is a prim op
106106
TORCHTRT_THROW_ERROR(
107107
"Unable to retrieve all node inputs for node: "
108-
<< util::node_info(n) << " (ctx.AddLayer)\nSpecifically failed to retrieve value for input: " << *input_node);
108+
<< util::node_info(n) << " (ctx.AddLayer)\nSpecifically failed to retrieve value for input: %"
109+
<< input->debugName());
109110
}
110111
}
111112

@@ -534,17 +535,23 @@ bool VerifyConverterSupportForBlock(const torch::jit::Block* b, bool suppress_er
534535
if (unsupported_ops.size() != 0) {
535536
std::stringstream unsupported_msg;
536537
unsupported_msg
537-
<< "Method requested cannot be compiled by Torch-TensorRT.TorchScript.\nUnsupported operators listed below:"
538+
<< "Method requested cannot be compiled end to end by Torch-TensorRT.TorchScript.\nUnsupported operators listed below:"
538539
<< std::endl;
539540
for (auto s : unsupported_ops) {
540541
unsupported_msg << " - " << s.second << std::endl;
541542
}
542-
unsupported_msg << "You can either implement converters for these ops in your application or request implementation"
543-
<< std::endl;
544-
unsupported_msg << "https://www.github.com/nvidia/Torch-TensorRT/issues" << std::endl;
545-
unsupported_msg << std::endl << "In Module:" << std::endl;
546543

547-
LOG_DEBUG(unsupported_msg.str());
544+
if (!suppress_errors) {
545+
unsupported_msg
546+
<< "You can either implement converters for these ops in your application or request implementation"
547+
<< std::endl;
548+
unsupported_msg << "https://www.github.com/nvidia/Torch-TensorRT/issues" << std::endl;
549+
unsupported_msg << std::endl << "In Module:" << std::endl;
550+
551+
LOG_ERROR(unsupported_msg.str());
552+
} else {
553+
LOG_INFO(unsupported_msg.str());
554+
}
548555

549556
std::unordered_map<std::string, std::unordered_set<std::string>> unsupported_node_locations;
550557
for (const auto n : b->nodes()) {
@@ -569,8 +576,12 @@ bool VerifyConverterSupportForBlock(const torch::jit::Block* b, bool suppress_er
569576
for (const auto& str : type.second) {
570577
traceback << str;
571578
}
579+
580+
auto tb_str = traceback.str();
572581
if (!suppress_errors) {
573-
LOG_ERROR(traceback.str());
582+
LOG_ERROR(tb_str);
583+
} else {
584+
LOG_DEBUG(tb_str);
574585
}
575586
}
576587

‎core/conversion/evaluators/aten.cpp

Lines changed: 13 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -1,3 +1,5 @@
1+
#include <math.h>
2+
13
#include "ATen/core/List.h"
24
#include "ATen/core/functional.h"
35
#include "ATen/core/ivalue.h"
@@ -98,6 +100,17 @@ DEFINE_GENERIC_TWO_INPUT_EVALUATOR(
98100
"aten::ge.float_int(float a, int b) -> (bool)",
99101
}));
100102

103+
DEFINE_ARITHMATIC_TWO_INPUT_EVALUATOR(
104+
pow,
105+
"aten::pow",
106+
pow(a, b),
107+
std::set<std::string>({
108+
"aten::pow.int(int a, int b) -> (float)",
109+
"aten::pow.float(float a, float b) -> (float)",
110+
"aten::pow.int_float(int a, float b) -> (float)",
111+
"aten::pow.float_int(float a, int b) -> (float)",
112+
}));
113+
101114
DEFINE_TWO_INPUT_SIMPLE_EVALUATOR(
102115
and,
103116
"aten::__and__",

‎core/conversion/evaluators/eval_macros.h

Lines changed: 47 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -77,6 +77,53 @@
7777
}, \
7878
EvalOptions().validSchemas(schemas)});
7979

80+
#define DEFINE_ARITHMATIC_TWO_INPUT_EVALUATOR(name, node_kind, operation, schemas) \
81+
auto name##_registrations TORCHTRT_UNUSED = RegisterNodeEvaluators().evaluator( \
82+
{c10::Symbol::fromQualString(node_kind), \
83+
[](const torch::jit::Node* n, kwargs& args) -> c10::optional<torch::jit::IValue> { \
84+
if (args.at(n->input(0)).IValue()->isInt()) { \
85+
auto a = args.at(n->input(0)).unwrapToInt(); \
86+
if (args.at(n->input(1)).IValue()->isInt()) { \
87+
auto b = args.at(n->input(1)).unwrapToInt(); \
88+
return operation; \
89+
} else if (args.at(n->input(1)).IValue()->isDouble()) { \
90+
auto b = args.at(n->input(1)).unwrapToDouble(); \
91+
return operation; \
92+
} else if (args.at(n->input(1)).IValue()->isBool()) { \
93+
auto b = args.at(n->input(1)).unwrapToBool(); \
94+
return operation; \
95+
} else { \
96+
TORCHTRT_THROW_ERROR( \
97+
"Unimplemented data type for " \
98+
<< node_kind << " evaluator b arg:" << args.at(n->input(1)).IValue()->type()->str()); \
99+
return {}; \
100+
} \
101+
} else if (args.at(n->input(0)).IValue()->isDouble()) { \
102+
auto a = args.at(n->input(0)).unwrapToDouble(); \
103+
if (args.at(n->input(1)).IValue()->isInt()) { \
104+
auto b = args.at(n->input(1)).unwrapToInt(); \
105+
return operation; \
106+
} else if (args.at(n->input(1)).IValue()->isDouble()) { \
107+
auto b = args.at(n->input(1)).unwrapToDouble(); \
108+
return operation; \
109+
} else if (args.at(n->input(1)).IValue()->isBool()) { \
110+
auto b = args.at(n->input(1)).unwrapToBool(); \
111+
return operation; \
112+
} else { \
113+
TORCHTRT_THROW_ERROR( \
114+
"Unimplemented data type for " \
115+
<< node_kind << " evaluator b arg:" << args.at(n->input(1)).IValue()->type()->str()); \
116+
return {}; \
117+
} \
118+
} else { \
119+
TORCHTRT_THROW_ERROR( \
120+
"Unimplemented data type for " \
121+
<< node_kind << " evaluator a arg: " << args.at(n->input(0)).IValue()->type()->str()); \
122+
return {}; \
123+
} \
124+
}, \
125+
EvalOptions().validSchemas(schemas)});
126+
80127
#define DEFINE_TWO_INPUT_SIMPLE_EVALUATOR(node_kind, node_name, operation, type, schemas) \
81128
auto node_kind##_registrations TORCHTRT_UNUSED = RegisterNodeEvaluators().evaluator( \
82129
{c10::Symbol::fromQualString(node_name), \

‎notebooks/Resnet50-example.ipynb

Lines changed: 6 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -26,7 +26,7 @@
2626
"cell_type": "markdown",
2727
"metadata": {},
2828
"source": [
29-
"<img src=\"http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
29+
"<img src=\"https://developer.download.nvidia.com/tesla/notebook_assets/nv_logo_torch_trt_resnet_notebook.png\" style=\"width: 90px; float: right;\">\n",
3030
"\n",
3131
"# Torch-TensorRT Getting Started - ResNet 50"
3232
]
@@ -63,7 +63,9 @@
6363
{
6464
"cell_type": "code",
6565
"execution_count": 2,
66-
"metadata": {},
66+
"metadata": {
67+
"collapsed": true
68+
},
6769
"outputs": [
6870
{
6971
"name": "stdout",
@@ -214,7 +216,7 @@
214216
"cell_type": "code",
215217
"execution_count": 3,
216218
"metadata": {
217-
"scrolled": true
219+
"collapsed": true
218220
},
219221
"outputs": [
220222
{
@@ -446,7 +448,7 @@
446448
"cell_type": "code",
447449
"execution_count": 4,
448450
"metadata": {
449-
"scrolled": true
451+
"collapsed": true
450452
},
451453
"outputs": [
452454
{

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