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Posted to commits@tvm.apache.org by GitBox <gi...@apache.org> on 2020/12/02 20:27:33 UTC
[GitHub] [tvm] codeislife99 opened a new pull request #7016: Fix trt Test
codeislife99 opened a new pull request #7016:
URL: https://github.com/apache/tvm/pull/7016
Fix TRT Test
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[GitHub] [tvm] trevor-m commented on a change in pull request #7016: Fix trt Test
Posted by GitBox <gi...@apache.org>.
trevor-m commented on a change in pull request #7016:
URL: https://github.com/apache/tvm/pull/7016#discussion_r534501808
##########
File path: tests/python/contrib/test_tensorrt.py
##########
@@ -1050,26 +1050,26 @@ def test_tensorrt_dynamic_batch():
batches_to_test = [1, 1, 0, 2, 3, 0, 1, 3, 2]
x_shape = (relay.Any(), 1, 8, 8)
x_data = np.ones([max(batches_to_test)] + list(x_shape)[1:]).astype("float32")
- result_dict = {}
for use_trt in [True, False]:
+ result_dict = {}
x = relay.var("x", shape=x_shape, dtype="float32")
out = relay.nn.relu(x)
f = relay.Function([x], out)
mod = tvm.IRModule()
mod["main"] = f
if use_trt:
- mod = relay.tensorrt.EnableTrt(mod)
+ mod, _ = tensorrt.partition_for_tensorrt(mod)
if not skip_runtime_test():
with relay.build_config(opt_level=3):
relay_exec = relay.create_executor("vm", mod=mod, ctx=tvm.cpu(0), target="llvm")
for i, batch_size in enumerate(batches_to_test):
- result_dict[(i, use_trt)] = relay_exec.evaluate()(x_data[:batch_size, ...])
+ result_dict[use_trt] = relay_exec.evaluate()(x_data[:batch_size, ...])
Review comment:
I think we still need to include `i` in the result dict, otherwise the results from all TRT runs will overwrite eachother and we are only looking at the last run
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[GitHub] [tvm] trevor-m commented on a change in pull request #7016: Fix trt Test
Posted by GitBox <gi...@apache.org>.
trevor-m commented on a change in pull request #7016:
URL: https://github.com/apache/tvm/pull/7016#discussion_r534475764
##########
File path: tests/python/contrib/test_tensorrt.py
##########
@@ -1058,7 +1058,7 @@ def test_tensorrt_dynamic_batch():
mod = tvm.IRModule()
mod["main"] = f
if use_trt:
- mod = relay.tensorrt.EnableTrt(mod)
+ mod = tensorrt.partition_for_tensorrt(mod, params)
Review comment:
I don't think this model has params
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[GitHub] [tvm] trevor-m commented on a change in pull request #7016: Fix trt Test
Posted by GitBox <gi...@apache.org>.
trevor-m commented on a change in pull request #7016:
URL: https://github.com/apache/tvm/pull/7016#discussion_r534501808
##########
File path: tests/python/contrib/test_tensorrt.py
##########
@@ -1050,26 +1050,26 @@ def test_tensorrt_dynamic_batch():
batches_to_test = [1, 1, 0, 2, 3, 0, 1, 3, 2]
x_shape = (relay.Any(), 1, 8, 8)
x_data = np.ones([max(batches_to_test)] + list(x_shape)[1:]).astype("float32")
- result_dict = {}
for use_trt in [True, False]:
+ result_dict = {}
x = relay.var("x", shape=x_shape, dtype="float32")
out = relay.nn.relu(x)
f = relay.Function([x], out)
mod = tvm.IRModule()
mod["main"] = f
if use_trt:
- mod = relay.tensorrt.EnableTrt(mod)
+ mod, _ = tensorrt.partition_for_tensorrt(mod)
if not skip_runtime_test():
with relay.build_config(opt_level=3):
relay_exec = relay.create_executor("vm", mod=mod, ctx=tvm.cpu(0), target="llvm")
for i, batch_size in enumerate(batches_to_test):
- result_dict[(i, use_trt)] = relay_exec.evaluate()(x_data[:batch_size, ...])
+ result_dict[use_trt] = relay_exec.evaluate()(x_data[:batch_size, ...])
Review comment:
I think we still need to include `i` in the result dict
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[GitHub] [tvm] anijain2305 commented on pull request #7016: Fix trt Test
Posted by GitBox <gi...@apache.org>.
anijain2305 commented on pull request #7016:
URL: https://github.com/apache/tvm/pull/7016#issuecomment-737649557
Thanks @codeislife99 @trevor-m This is merged
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[GitHub] [tvm] anijain2305 merged pull request #7016: Fix trt Test
Posted by GitBox <gi...@apache.org>.
anijain2305 merged pull request #7016:
URL: https://github.com/apache/tvm/pull/7016
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