diff --git a/docker/install/ubuntu_install_onnx.sh b/docker/install/ubuntu_install_onnx.sh index 631ecbda03be..d9ad7bb451a6 100755 --- a/docker/install/ubuntu_install_onnx.sh +++ b/docker/install/ubuntu_install_onnx.sh @@ -27,14 +27,13 @@ set -o pipefail # https://github.com/onnx/onnx/pull/2834). When updating the CI image # to onnx>=1.9, onnxoptimizer should also be installed. pip3 install \ - onnx==1.10.2 \ - onnxruntime==1.9.0 \ - onnxoptimizer==0.2.6 - + onnx==1.8.1 \ + onnxruntime==1.7.0 + # torch depends on a number of other packages, but unhelpfully, does # not expose that in the wheel!!! pip3 install future pip3 install \ - torch==1.7.0 \ - torchvision==0.8.1 + torch==1.10.1 \ + torchvision==0.11.2 diff --git a/python/tvm/relay/frontend/pytorch.py b/python/tvm/relay/frontend/pytorch.py index fbc5f6e59dc9..319062ddea41 100644 --- a/python/tvm/relay/frontend/pytorch.py +++ b/python/tvm/relay/frontend/pytorch.py @@ -23,6 +23,7 @@ import itertools import math import sys +import logging import numpy as np import tvm diff --git a/tests/python/frontend/onnx/test_forward.py b/tests/python/frontend/onnx/test_forward.py index 701906e4be40..4fac42ad227c 100644 --- a/tests/python/frontend/onnx/test_forward.py +++ b/tests/python/frontend/onnx/test_forward.py @@ -4967,38 +4967,11 @@ def verify_eyelike(indata): ) unsupported_onnx_tests = [ - "test_basic_convinteger", - "test_batchnorm_epsilon_training_mode", - "test_batchnorm_example_training_mode", - "test_bernoulli", - "test_bernoulli_expanded", - "test_bernoulli_double", - "test_bernoulli_double_expanded", - "test_bernoulli_seed", - "test_bernoulli_seed_expanded", "test_cast_BFLOAT16_to_FLOAT", "test_cast_DOUBLE_to_FLOAT16", "test_cast_FLOAT_to_BFLOAT16", "test_cast_FLOAT_to_STRING", "test_cast_STRING_to_FLOAT", - "test_castlike_BFLOAT16_to_FLOAT", - "test_castlike_BFLOAT16_to_FLOAT_expanded", - "test_castlike_DOUBLE_to_FLOAT", - "test_castlike_DOUBLE_to_FLOAT16", - "test_castlike_DOUBLE_to_FLOAT16_expanded", - "test_castlike_FLOAT16_to_DOUBLE", - "test_castlike_FLOAT16_to_FLOAT", - "test_castlike_FLOAT_to_BFLOAT16", - "test_castlike_FLOAT_to_BFLOAT16_expanded", - "test_castlike_FLOAT_to_DOUBLE", - "test_castlike_FLOAT_to_FLOAT16", - "test_castlike_FLOAT_to_STRING", - "test_castlike_FLOAT_to_STRING_expanded", - "test_castlike_STRING_to_FLOAT", - "test_castlike_STRING_to_FLOAT_expanded", - "test_convinteger_with_padding", - "test_convinteger_without_padding", - "test_convtranspose_autopad_same", "test_convtranspose_dilations", "test_convtranspose_output_shape", "test_cumsum_1d", @@ -5014,13 +4987,9 @@ def verify_eyelike(indata): "test_dropout_default_mask", "test_dropout_default_mask_ratio", "test_dropout_default_ratio", - "test_gru_batchwise", - "test_hardswish", - "test_identity_sequence", "test_if_seq", "test_loop11", "test_loop13_seq", - "test_lstm_batchwise", "test_matmulinteger", "test_maxpool_2d_same_lower", "test_maxpool_2d_same_upper", @@ -5030,10 +4999,6 @@ def verify_eyelike(indata): "test_mvn", # This test fails llvm with a lowering error: "test_nllloss_NCd1d2d3_none_no_weight_negative_ii_expanded", - "test_optional_has_element", - "test_optional_get_element", - "test_optional_get_element_sequence", - "test_optional_has_element_empty", "test_qlinearmatmul_3D", "test_range_float_type_positive_delta_expanded", "test_range_int32_type_negative_delta_expanded", @@ -5051,13 +5016,6 @@ def verify_eyelike(indata): "test_round", "test_sequence_insert_at_back", "test_sequence_insert_at_front", - "test_shape_end_1", - "test_shape_end_negative_1", - "test_shape_start_1", - "test_shape_start_1_end_2", - "test_shape_start_1_end_negative_1", - "test_shape_start_negative_1", - "test_simple_rnn_batchwise", "test_simple_rnn_defaults", "test_simple_rnn_with_initial_bias", "test_split_variable_parts_1d", @@ -5083,24 +5041,6 @@ def verify_eyelike(indata): "test_training_dropout_mask", "test_training_dropout_zero_ratio", "test_training_dropout_zero_ratio_mask", - "test_tril", - "test_tril_pos", - "test_tril_square", - "test_tril_square_neg", - "test_tril_neg", - "test_tril_one_row_neg", - "test_tril_out_neg", - "test_tril_out_pos", - "test_tril_zero", - "test_triu", - "test_triu_one_row", - "test_triu_out_neg_out", - "test_triu_out_pos", - "test_triu_neg", - "test_triu_pos", - "test_triu_square", - "test_triu_square_neg", - "test_triu_zero", # These unsqueeze tests work, but take 2+ hrs to run "test_unsqueeze_three_axes", "test_unsqueeze_two_axes", diff --git a/tests/python/frontend/pytorch/test_forward.py b/tests/python/frontend/pytorch/test_forward.py index 0692ab879c7a..86970bfb6d4d 100644 --- a/tests/python/frontend/pytorch/test_forward.py +++ b/tests/python/frontend/pytorch/test_forward.py @@ -212,7 +212,10 @@ def verify_model( compiled_input = dict(zip(input_names, [inp.clone().cpu().numpy() for inp in baseline_input])) with tvm.transform.PassContext(opt_level=3): - for target, dev in tvm.testing.enabled_targets(): + for target in ["llvm", "cuda"]: + if not tvm.runtime.enabled(target): + continue + dev = tvm.device(target, 0) relay_graph, relay_lib, relay_params = relay.build(mod, target=target, params=params) relay_model = graph_executor.create(relay_graph, relay_lib, dev) relay_model.set_input(**relay_params) @@ -2196,7 +2199,7 @@ def test_3d_models(): def _get_default_vm_targets(): - return [tgt for (tgt, _) in tvm.testing.enabled_targets()] + return ["llvm", "cuda"] def verify_script_model(pt_model, ishapes, targets, idtype=None): @@ -2269,7 +2272,10 @@ def verify_model_vm(input_model, ishapes, idtype=None, idata=None, targets=["llv mod, params = relay.frontend.from_pytorch(input_model, input_shapes) for tgt in targets: + if not tvm.runtime.enabled(tgt): + continue print("Running on target", tgt) + dev = tvm.device(tgt, 0) evaluator = relay.create_executor("vm", mod=mod, device=dev, target=tgt).evaluate() @@ -3897,7 +3903,7 @@ def test_fn(x, mask): for shape in [(10,), (3, 4), (16, 32, 64)]: x = torch.randn(*shape) mask = x.ge(0.5) - verify_trace_model(test_fn, [x, mask], ["llvm", "cuda", "nvptx"]) + verify_trace_model(test_fn, [x, mask], ["llvm", "cuda"]) def test_unique(): @@ -3905,7 +3911,7 @@ def test_fn(is_sorted, return_inverse, return_counts): return lambda x: torch.unique(x, is_sorted, return_inverse, return_counts) in_data = torch.randint(0, 20, (10,), dtype=torch.int32) - targets = ["llvm", "cuda", "nvptx"] + targets = ["llvm", "cuda"] verify_trace_model(test_fn(True, True, True), [in_data], targets) verify_trace_model(test_fn(True, False, True), [in_data], targets) verify_trace_model(test_fn(True, True, False), [in_data], targets)