diff --git a/CMakeLists.txt b/CMakeLists.txt index 2f987d872a55..88222b46f33d 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -132,6 +132,12 @@ if(MSVC) add_compile_options(/wd4180) # DLL interface warning in c++ add_compile_options(/wd4251) + # destructor was implicitly defined as deleted + add_compile_options(/wd4624) + # unary minus operator applied to unsigned type, result still unsigned + add_compile_options(/wd4146) + # 'inline': used more than once + add_compile_options(/wd4141) else(MSVC) if(USE_TF_COMPILE_FLAGS) diff --git a/apps/cpp_rpc/CMakeLists.txt b/apps/cpp_rpc/CMakeLists.txt index ad8ae1488498..ccac53fc3ca0 100644 --- a/apps/cpp_rpc/CMakeLists.txt +++ b/apps/cpp_rpc/CMakeLists.txt @@ -1,4 +1,6 @@ -set(TVM_RPC_SOURCES +cmake_policy(SET CMP0069 NEW) # suppress cmake warning about IPO + +set(TVM_RPC_SOURCES main.cc rpc_env.cc rpc_server.cc @@ -11,7 +13,12 @@ endif() # Set output to same directory as the other TVM libs set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}) add_executable(tvm_rpc ${TVM_RPC_SOURCES}) -set_property(TARGET tvm_rpc PROPERTY INTERPROCEDURAL_OPTIMIZATION_RELEASE TRUE) + +include(CheckIPOSupported) +check_ipo_supported(RESULT result OUTPUT output) +if(result) + set_property(TARGET tvm_rpc PROPERTY INTERPROCEDURAL_OPTIMIZATION_RELEASE TRUE) +endif() if(WIN32) target_compile_definitions(tvm_rpc PUBLIC -DNOMINMAX) @@ -35,5 +42,5 @@ target_include_directories( PUBLIC DLPACK_PATH PUBLIC DMLC_PATH ) - -target_link_libraries(tvm_rpc tvm_runtime) \ No newline at end of file + +target_link_libraries(tvm_rpc tvm_runtime) diff --git a/cmake/modules/LibInfo.cmake b/cmake/modules/LibInfo.cmake index deaa6d9d8362..131dceeb345d 100644 --- a/cmake/modules/LibInfo.cmake +++ b/cmake/modules/LibInfo.cmake @@ -75,6 +75,7 @@ function(add_lib_info src_file) TVM_INFO_USE_ARM_COMPUTE_LIB="${USE_ARM_COMPUTE_LIB}" TVM_INFO_USE_ARM_COMPUTE_LIB_GRAPH_RUNTIME="${USE_ARM_COMPUTE_LIB_GRAPH_RUNTIME}" TVM_INFO_INDEX_DEFAULT_I64="${INDEX_DEFAULT_I64}" + TVM_CXX_COMPILER_PATH="${CMAKE_CXX_COMPILER}" ) endfunction() diff --git a/cmake/utils/FindLLVM.cmake b/cmake/utils/FindLLVM.cmake index b8c5bf815bf5..9fc4df24b813 100644 --- a/cmake/utils/FindLLVM.cmake +++ b/cmake/utils/FindLLVM.cmake @@ -120,7 +120,7 @@ macro(find_llvm use_llvm) string(STRIP ${TVM_LLVM_VERSION} TVM_LLVM_VERSION) # definitions string(REGEX MATCHALL "(^| )-D[A-Za-z0-9_]*" __llvm_defs ${__llvm_cxxflags}) - set(LLVM_DEFINTIIONS "") + set(LLVM_DEFINITIONS "") foreach(__flag IN ITEMS ${__llvm_defs}) string(STRIP "${__flag}" __llvm_def) list(APPEND LLVM_DEFINITIONS "${__llvm_def}") diff --git a/conda/build-environment.yaml b/conda/build-environment.yaml index 31b39bfafcd0..7c7831e25b1b 100644 --- a/conda/build-environment.yaml +++ b/conda/build-environment.yaml @@ -35,3 +35,4 @@ dependencies: - bzip2 - make - scipy + - pillow diff --git a/python/tvm/auto_scheduler/cost_model/xgb_model.py b/python/tvm/auto_scheduler/cost_model/xgb_model.py index aab36c175c3c..3cf65954be7f 100644 --- a/python/tvm/auto_scheduler/cost_model/xgb_model.py +++ b/python/tvm/auto_scheduler/cost_model/xgb_model.py @@ -116,11 +116,13 @@ def __init__( if xgb is None: xgb = __import__("xgboost") except ImportError: + # add "from Node" to silence + # "During handling of the above exception, another exception occurred" raise ImportError( "XGBoost is required for XGBModel. " "Please install its python package first. " "Help: (https://xgboost.readthedocs.io/en/latest/) " - ) + ) from None self.xgb_params = { "max_depth": 10, diff --git a/python/tvm/contrib/cc.py b/python/tvm/contrib/cc.py index 9643d9b650fd..59a1d11216ee 100644 --- a/python/tvm/contrib/cc.py +++ b/python/tvm/contrib/cc.py @@ -47,7 +47,7 @@ def create_shared(output, objects, options=None, cc="g++"): ): _linux_compile(output, objects, options, cc, compile_shared=True) elif sys.platform == "win32": - _windows_shared(output, objects, options) + _windows_compile(output, objects, options) else: raise ValueError("Unsupported platform") @@ -71,6 +71,8 @@ def create_executable(output, objects, options=None, cc="g++"): """ if sys.platform == "darwin" or sys.platform.startswith("linux"): _linux_compile(output, objects, options, cc) + elif sys.platform == "win32": + _windows_compile(output, objects, options) else: raise ValueError("Unsupported platform") @@ -212,9 +214,9 @@ def _linux_compile(output, objects, options, compile_cmd="g++", compile_shared=F raise RuntimeError(msg) -def _windows_shared(output, objects, options): +def _windows_compile(output, objects, options): cmd = ["clang"] - cmd += ["-O2", "-flto=full", "-fuse-ld=lld-link"] + cmd += ["-O2"] if output.endswith(".so") or output.endswith(".dll"): cmd += ["-shared"] @@ -240,6 +242,7 @@ def _windows_shared(output, objects, options): ) if proc.returncode != 0: msg = "Compilation error:\n" + msg += " ".join(cmd) + "\n" msg += py_str(out) raise RuntimeError(msg) diff --git a/python/tvm/contrib/nvcc.py b/python/tvm/contrib/nvcc.py index 5886760934fb..2a97b0b31d1e 100644 --- a/python/tvm/contrib/nvcc.py +++ b/python/tvm/contrib/nvcc.py @@ -89,6 +89,12 @@ def compile_cuda(code, target="ptx", arch=None, options=None, path_target=None): cmd += ["-o", file_target] cmd += [temp_code] + cxx_compiler_path = tvm.support.libinfo().get("TVM_CXX_COMPILER_PATH") + if cxx_compiler_path != "": + # This tells nvcc where to find the c++ compiler just in case it is not in the path. + # On Windows it is not in the path by default. + cmd += ["-ccbin", cxx_compiler_path] + proc = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) (out, _) = proc.communicate() diff --git a/src/auto_scheduler/search_policy/sketch_policy.cc b/src/auto_scheduler/search_policy/sketch_policy.cc index 91721afdba74..4a4ab18b5eed 100644 --- a/src/auto_scheduler/search_policy/sketch_policy.cc +++ b/src/auto_scheduler/search_policy/sketch_policy.cc @@ -519,7 +519,7 @@ Array SketchPolicyNode::EvolutionarySearch(const Array& init_popul // auxiliary global variables std::vector pop_scores; std::vector pop_selection_probs; - float max_score = -1e-10; + float max_score = -1e-10f; pop_scores.reserve(population); pop_selection_probs.reserve(population); std::uniform_real_distribution<> dis(0.0, 1.0); diff --git a/src/support/libinfo.cc b/src/support/libinfo.cc index c8aa76b9d1f5..0f394f50fe71 100644 --- a/src/support/libinfo.cc +++ b/src/support/libinfo.cc @@ -208,6 +208,10 @@ #define TVM_INFO_INDEX_DEFAULT_I64 "NOT-FOUND" #endif +#ifndef TVM_CXX_COMPILER_PATH +#define TVM_CXX_COMPILER_PATH "" +#endif + namespace tvm { /*! @@ -262,7 +266,8 @@ TVM_DLL Map GetLibInfo() { {"USE_TARGET_ONNX", TVM_INFO_USE_TARGET_ONNX}, {"USE_ARM_COMPUTE_LIB", TVM_INFO_USE_ARM_COMPUTE_LIB}, {"USE_ARM_COMPUTE_LIB_GRAPH_RUNTIME", TVM_INFO_USE_ARM_COMPUTE_LIB_GRAPH_RUNTIME}, - {"INDEX_DEFAULT_I64", TVM_INFO_INDEX_DEFAULT_I64}}; + {"INDEX_DEFAULT_I64", TVM_INFO_INDEX_DEFAULT_I64}, + {"TVM_CXX_COMPILER_PATH", TVM_CXX_COMPILER_PATH}}; return result; } diff --git a/src/target/source/codegen_c_host.cc b/src/target/source/codegen_c_host.cc index bee5441649c5..3ec64ed2ace9 100644 --- a/src/target/source/codegen_c_host.cc +++ b/src/target/source/codegen_c_host.cc @@ -44,6 +44,7 @@ void CodeGenCHost::Init(bool output_ssa, bool emit_asserts, std::string target_s emit_asserts_ = emit_asserts; declared_globals_.clear(); decl_stream << "// tvm target: " << target_str << "\n"; + decl_stream << "#define TVM_EXPORTS\n"; decl_stream << "#include \"tvm/runtime/c_runtime_api.h\"\n"; decl_stream << "#include \"tvm/runtime/c_backend_api.h\"\n"; decl_stream << "#include \n"; diff --git a/src/target/source/codegen_cuda.cc b/src/target/source/codegen_cuda.cc index e5547315613f..35b94f55e4e4 100644 --- a/src/target/source/codegen_cuda.cc +++ b/src/target/source/codegen_cuda.cc @@ -79,6 +79,20 @@ std::string CodeGenCUDA::Finish() { decl_stream << "#include \n"; } + decl_stream << "\n#ifdef _WIN32\n"; + decl_stream << " using uint = unsigned int;\n"; + decl_stream << " using uchar = unsigned char;\n"; + decl_stream << " using ushort = unsigned short;\n"; + decl_stream << " using int64_t = long long;\n"; + decl_stream << " using uint64_t = unsigned long long;\n"; + decl_stream << "#else\n"; + decl_stream << " #define uint unsigned int\n"; + decl_stream << " #define uchar unsigned char\n"; + decl_stream << " #define ushort unsigned short\n"; + decl_stream << " #define int64_t long\n"; + decl_stream << " #define uint64_t ulong\n"; + decl_stream << "#endif\n"; + return CodeGenC::Finish(); } @@ -99,7 +113,7 @@ void CodeGenCUDA::BindThreadIndex(const IterVar& iv) { void CodeGenCUDA::PrintType(DataType t, std::ostream& os) { // NOLINT(*) int lanes = t.lanes(); if (t.is_handle()) { - ICHECK_EQ(lanes, 1) << "do not yet support vector types"; + ICHECK(t.is_scalar()) << "do not yet support vector types"; os << "void*"; return; } @@ -108,7 +122,7 @@ void CodeGenCUDA::PrintType(DataType t, std::ostream& os) { // NOLINT(*) switch (t.bits()) { case 16: enable_fp16_ = true; - if (lanes == 1) { + if (t.is_scalar()) { os << "half"; } else if (lanes <= 8) { // Emit CUDA code to access fp16 vector elements. @@ -136,7 +150,7 @@ void CodeGenCUDA::PrintType(DataType t, std::ostream& os) { // NOLINT(*) fail = true; break; } - if (!fail && (lanes == 1 || t.bits() == 16)) return; + if (!fail && (t.is_scalar() || t.bits() == 16)) return; if (!fail && (lanes >= 2 && lanes <= 4)) { os << lanes; return; @@ -154,15 +168,11 @@ void CodeGenCUDA::PrintType(DataType t, std::ostream& os) { // NOLINT(*) } } else if (t.is_uint() || t.is_int()) { if (t.is_uint()) { - if (t.lanes() != 1) { - os << "u"; - } else { - os << "unsigned "; - } + os << "u"; } switch (t.bits()) { case 1: { - if (t.lanes() == 1) { + if (t.is_scalar()) { os << "int"; return; } else if (t.lanes() == 8) { @@ -179,7 +189,7 @@ void CodeGenCUDA::PrintType(DataType t, std::ostream& os) { // NOLINT(*) } } case 4: { - if (t.lanes() == 1) { + if (t.is_scalar()) { os << "int"; return; } else if (t.lanes() == 4) { @@ -220,7 +230,7 @@ void CodeGenCUDA::PrintType(DataType t, std::ostream& os) { // NOLINT(*) enable_int8_ = true; os << "int4"; return; - } else if (!t.is_uint() && t.lanes() == 1) { + } else if (!t.is_uint() && t.is_scalar()) { os << "signed char"; break; } else { @@ -235,22 +245,16 @@ void CodeGenCUDA::PrintType(DataType t, std::ostream& os) { // NOLINT(*) os << "int"; break; case 64: { - if (sizeof(long) != 8) { // NOLINT(*) - if (t.lanes() == 1) { - os << "long long"; - break; - } else if (t.lanes() == 2) { - os << "longlong"; - break; - } else { - // No longlong3, longlong4 - LOG(FATAL) << "Cannot convert type " << t << " to CUDA type on a L32 platform"; - break; - } - } else { - os << "long"; - break; + if (t.is_scalar()) { + os << "int64_t"; + } else if (t.lanes() == 2) { + os << "longlong2"; + } else if (t.lanes() == 3) { + os << "longlong3"; + } else if (t.lanes() == 4) { + os << "longlong4"; } + return; } default: fail = true; diff --git a/tests/python/conftest.py b/tests/python/conftest.py new file mode 100644 index 000000000000..e8042c8f5095 --- /dev/null +++ b/tests/python/conftest.py @@ -0,0 +1,42 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +import sys +import tvm + +collect_ignore = [] +if sys.platform.startswith("win"): + collect_ignore.append("frontend/caffe") + collect_ignore.append("frontend/caffe2") + collect_ignore.append("frontend/coreml") + collect_ignore.append("frontend/darknet") + collect_ignore.append("frontend/keras") + collect_ignore.append("frontend/mxnet") + collect_ignore.append("frontend/pytorch") + collect_ignore.append("frontend/tensorflow") + collect_ignore.append("frontend/tflite") + collect_ignore.append("frontend/onnx") + collect_ignore.append("driver/tvmc/test_autoscheduler.py") + collect_ignore.append("unittest/test_auto_scheduler_cost_model.py") # stack overflow + # collect_ignore.append("unittest/test_auto_scheduler_measure.py") # exception ignored + collect_ignore.append("unittest/test_auto_scheduler_search_policy.py") # stack overflow + # collect_ignore.append("unittest/test_auto_scheduler_measure.py") # exception ignored + + collect_ignore.append("unittest/test_tir_intrin.py") + +if tvm.support.libinfo().get("USE_MICRO", "OFF") != "ON": + collect_ignore.append("unittest/test_micro_transport.py") diff --git a/tests/python/driver/tvmc/test_common.py b/tests/python/driver/tvmc/test_tvmc_common.py similarity index 100% rename from tests/python/driver/tvmc/test_common.py rename to tests/python/driver/tvmc/test_tvmc_common.py diff --git a/tests/python/relay/test_auto_scheduler_layout_rewrite.py b/tests/python/relay/test_auto_scheduler_layout_rewrite_networks.py similarity index 100% rename from tests/python/relay/test_auto_scheduler_layout_rewrite.py rename to tests/python/relay/test_auto_scheduler_layout_rewrite_networks.py diff --git a/tests/python/unittest/test_auto_scheduler_cost_model.py b/tests/python/unittest/test_auto_scheduler_cost_model.py index 36360da45c8d..0b34615583db 100644 --- a/tests/python/unittest/test_auto_scheduler_cost_model.py +++ b/tests/python/unittest/test_auto_scheduler_cost_model.py @@ -68,14 +68,15 @@ def test_xgb_model(): assert rmse <= 0.3 # test loading a record file - with tempfile.NamedTemporaryFile() as fp: - auto_scheduler.save_records(fp.name, inputs, results) - model.update_from_file(fp.name) + tmpdir = tvm.contrib.utils.tempdir() + tmpfile = tmpdir.relpath("test1") + auto_scheduler.save_records(tmpfile, inputs, results) + model.update_from_file(tmpfile) # test model serialization - with tempfile.NamedTemporaryFile() as fp: - model.save(fp.name) - model.load(fp.name) + tmpfile = tmpdir.relpath("test2") + model.save(tmpfile) + model.load(tmpfile) if __name__ == "__main__": diff --git a/tests/python/unittest/test_crt.py b/tests/python/unittest/test_crt.py index 4b744b8ee10a..1bd24c931b72 100644 --- a/tests/python/unittest/test_crt.py +++ b/tests/python/unittest/test_crt.py @@ -19,7 +19,9 @@ import copy import glob import os -import pty +import pytest + +pytest.importorskip("pty") import sys import subprocess import textwrap diff --git a/tests/python/unittest/test_custom_datatypes.py b/tests/python/unittest/test_custom_datatypes.py index 6aad93abd510..75e807456981 100644 --- a/tests/python/unittest/test_custom_datatypes.py +++ b/tests/python/unittest/test_custom_datatypes.py @@ -21,7 +21,6 @@ import tvm.topi.testing import numpy as np import pytest -from numpy.random import MT19937, RandomState, SeedSequence from tvm import relay from tvm.relay.testing.layers import batch_norm_infer from tvm.target.datatype import ( @@ -66,7 +65,7 @@ def get_cat_image(dimensions): # we use a random seed to generate input_data # to guarantee stable tests -rs = RandomState(MT19937(SeedSequence(123456789))) +np.random.seed(0) def convert_ndarray(dst_dtype, array): @@ -341,7 +340,7 @@ def check_unary_op(op, src_dtype, dst_dtype, shape): t1 = relay.TensorType(shape, src_dtype) x = relay.var("x", t1) z = op(x) - x_data = rs.rand(*shape).astype(t1.dtype) + x_data = np.random.rand(*shape).astype(t1.dtype) module = tvm.IRModule.from_expr(relay.Function([x], z)) @@ -372,8 +371,8 @@ def check_binary_op(opfunc, src_dtype, dst_dtype): x = relay.var("x", t1) y = relay.var("y", t2) z = opfunc(x, y) - x_data = rs.rand(*shape1).astype(t1.dtype) - y_data = rs.rand(*shape2).astype(t2.dtype) + x_data = np.random.rand(*shape1).astype(t1.dtype) + y_data = np.random.rand(*shape2).astype(t2.dtype) module = tvm.IRModule.from_expr(relay.Function([x, y], z)) compare(module, (x_data, y_data), src_dtype, dst_dtype, rtol, atol) @@ -416,8 +415,8 @@ def run_test_conv2d( w = relay.var("w", shape=kshape, dtype=src_dtype) y = relay.nn.conv2d(x, w, padding=padding, dilation=dilation, groups=groups, **attrs) module = tvm.IRModule.from_expr(relay.Function([x, w], y)) - data = rs.uniform(-scale, scale, size=dshape).astype(src_dtype) - kernel = rs.uniform(-scale, scale, size=kshape).astype(src_dtype) + data = np.random.uniform(-scale, scale, size=dshape).astype(src_dtype) + kernel = np.random.uniform(-scale, scale, size=kshape).astype(src_dtype) compare(module, (data, kernel), src_dtype, dst_dtype, rtol, atol) @@ -497,7 +496,7 @@ def run_batchnorm(src_dtype, dst_dtype, rtol=1e-6, atol=1e-6): bn = batch_norm_infer(data=x, epsilon=2e-5, scale=False, name="bn_x") f = relay.Function(relay.analysis.free_vars(bn), bn) - x_data = rs.rand(*shape).astype(t.dtype) + x_data = np.random.rand(*shape).astype(t.dtype) module = tvm.IRModule.from_expr(f) zero_data = np.zeros((32), "float32") diff --git a/tests/python/unittest/test_micro_artifact.py b/tests/python/unittest/test_micro_artifact.py index d757f0956b81..fc180200720d 100644 --- a/tests/python/unittest/test_micro_artifact.py +++ b/tests/python/unittest/test_micro_artifact.py @@ -17,6 +17,7 @@ """Unit tests for the artifact module.""" +import pytest import json import os import shutil @@ -24,6 +25,8 @@ from tvm.contrib import utils +pytest.importorskip("tvm.micro") +from tvm.micro import artifact FILE_LIST = ["label1", "label2", "label12", "unlabelled"]