mirror of https://github.com/hpcaitech/ColossalAI
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201 lines
7.7 KiB
201 lines
7.7 KiB
import subprocess
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import click
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import torch
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from torch.utils.cpp_extension import CUDA_HOME
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import colossalai
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def to_click_output(val):
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# installation check output to understandable symbols for readability
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VAL_TO_SYMBOL = {True: u'\u2713', False: 'x', None: 'N/A'}
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if val in VAL_TO_SYMBOL:
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return VAL_TO_SYMBOL[val]
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else:
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return val
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def check_installation():
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"""
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This function will check the installation of colossalai, specifically, the version compatibility of
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colossalai, pytorch and cuda.
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Example:
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```text
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```
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Returns: A table of installation information.
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"""
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found_aot_cuda_ext = _check_aot_built_cuda_extension_installed()
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cuda_version = _check_cuda_version()
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torch_version, torch_cuda_version = _check_torch_version()
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colossalai_verison, torch_version_required, cuda_version_required = _parse_colossalai_version()
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# if cuda_version is None, that means either
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# CUDA_HOME is not found, thus cannot compare the version compatibility
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if not cuda_version:
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sys_torch_cuda_compatibility = None
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else:
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sys_torch_cuda_compatibility = _is_compatible([cuda_version, torch_cuda_version])
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# if cuda_version or cuda_version_required is None, that means either
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# CUDA_HOME is not found or AOT compilation is not enabled
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# thus, there is no need to compare the version compatibility at all
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if not cuda_version or not cuda_version_required:
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sys_colossalai_cuda_compatibility = None
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else:
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sys_colossalai_cuda_compatibility = _is_compatible([cuda_version, cuda_version_required])
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# if torch_version_required is None, that means AOT compilation is not enabled
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# thus there is no need to compare the versions
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if torch_version_required is None:
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torch_compatibility = None
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else:
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torch_compatibility = _is_compatible([torch_version, torch_version_required])
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click.echo(f'#### Installation Report ####')
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click.echo(f'\n------------ Environment ------------')
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click.echo(f"Colossal-AI version: {to_click_output(colossalai_verison)}")
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click.echo(f"PyTorch version: {to_click_output(torch_version)}")
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click.echo(f"CUDA version: {to_click_output(cuda_version)}")
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click.echo(f"CUDA version required by PyTorch: {to_click_output(torch_cuda_version)}")
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click.echo("")
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click.echo(f"Note:")
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click.echo(f"1. The table above checks the versions of the libraries/tools in the current environment")
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click.echo(f"2. If the CUDA version is N/A, you can set the CUDA_HOME environment variable to locate it")
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click.echo(f'\n------------ CUDA Extensions AOT Compilation ------------')
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click.echo(f"Found AOT CUDA Extension: {to_click_output(found_aot_cuda_ext)}")
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click.echo(f"PyTorch version used for AOT compilation: {to_click_output(torch_version_required)}")
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click.echo(f"CUDA version used for AOT compilation: {to_click_output(cuda_version_required)}")
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click.echo("")
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click.echo(f"Note:")
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click.echo(
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f"1. AOT (ahead-of-time) compilation of the CUDA kernels occurs during installation when the environment varialbe CUDA_EXT=1 is set"
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)
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click.echo(f"2. If AOT compilation is not enabled, stay calm as the CUDA kernels can still be built during runtime")
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click.echo(f"\n------------ Compatibility ------------")
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click.echo(f'PyTorch version match: {to_click_output(torch_compatibility)}')
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click.echo(f"System and PyTorch CUDA version match: {to_click_output(sys_torch_cuda_compatibility)}")
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click.echo(f"System and Colossal-AI CUDA version match: {to_click_output(sys_colossalai_cuda_compatibility)}")
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click.echo(f"")
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click.echo(f"Note:")
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click.echo(f"1. The table above checks the version compatibility of the libraries/tools in the current environment")
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click.echo(
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f" - PyTorch version mistach: whether the PyTorch version in the current environment is compatible with the PyTorch version used for AOT compilation"
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)
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click.echo(
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f" - System and PyTorch CUDA version match: whether the CUDA version in the current environment is compatible with the CUDA version required by PyTorch"
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)
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click.echo(
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f" - System and Colossal-AI CUDA version match: whether the CUDA version in the current environment is compatible with the CUDA version used for AOT compilation"
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)
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def _is_compatible(versions):
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"""
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Compare the list of versions and return whether they are compatible.
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"""
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if None in versions:
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return False
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# split version into [major, minor, patch]
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versions = [version.split('.') for version in versions]
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for version in versions:
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if len(version) == 2:
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# x means unknown
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version.append('x')
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for idx, version_values in enumerate(zip(*versions)):
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equal = len(set(version_values)) == 1
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if idx in [0, 1] and not equal:
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return False
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elif idx == 1:
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return True
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else:
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continue
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def _parse_colossalai_version():
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"""
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Get the Colossal-AI version information.
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Returns:
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colossalai_version: Colossal-AI version.
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torch_version_for_aot_build: PyTorch version used for AOT compilation of CUDA kernels.
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cuda_version_for_aot_build: CUDA version used for AOT compilation of CUDA kernels.
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"""
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# colossalai version can be in two formats
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# 1. X.X.X+torchX.XXcuXX.X (when colossalai is installed with CUDA extensions)
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# 2. X.X.X (when colossalai is not installed with CUDA extensions)
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# where X represents an integer.
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colossalai_verison = colossalai.__version__.split('+')[0]
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try:
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torch_version_for_aot_build = colossalai.__version__.split('torch')[1].split('cu')[0]
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cuda_version_for_aot_build = colossalai.__version__.split('cu')[1]
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except:
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torch_version_for_aot_build = None
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cuda_version_for_aot_build = None
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return colossalai_verison, torch_version_for_aot_build, cuda_version_for_aot_build
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def _check_aot_built_cuda_extension_installed():
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"""
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According to `op_builder/README.md`, the CUDA extension can be built with either
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AOT (ahead-of-time) or JIT (just-in-time) compilation.
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AOT compilation will build CUDA extensions to `colossalai._C` during installation.
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JIT (just-in-time) compilation will build CUDA extensions to `~/.cache/colossalai/torch_extensions` during runtime.
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"""
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try:
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import colossalai._C.fused_optim
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found_aot_cuda_ext = True
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except ImportError:
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found_aot_cuda_ext = False
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return found_aot_cuda_ext
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def _check_torch_version():
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"""
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Get the PyTorch version information.
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Returns:
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torch_version: PyTorch version.
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torch_cuda_version: CUDA version required by PyTorch.
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"""
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# get torch version
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torch_version = torch.__version__.split('+')[0]
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# get cuda version in pytorch build
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torch_cuda_major = torch.version.cuda.split(".")[0]
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torch_cuda_minor = torch.version.cuda.split(".")[1]
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torch_cuda_version = f'{torch_cuda_major}.{torch_cuda_minor}'
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return torch_version, torch_cuda_version
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def _check_cuda_version():
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"""
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Get the CUDA version information.
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Returns:
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cuda_version: CUDA version found on the system.
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"""
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# get cuda version
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if CUDA_HOME is None:
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cuda_version = CUDA_HOME
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else:
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raw_output = subprocess.check_output([CUDA_HOME + "/bin/nvcc", "-V"], universal_newlines=True)
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output = raw_output.split()
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release_idx = output.index("release") + 1
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release = output[release_idx].split(".")
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bare_metal_major = release[0]
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bare_metal_minor = release[1][0]
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cuda_version = f'{bare_metal_major}.{bare_metal_minor}'
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return cuda_version
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