#!/usr/bin/env python3 -u
# Copyright (c) DP Technology.
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
from torch.utils import cpp_extension
from torch.utils.cpp_extension import CUDAExtension, BuildExtension

import os
import subprocess
import sys

from setuptools import find_packages, setup

if sys.version_info < (3, 7):
    sys.exit("Sorry, Python >= 3.7 is required for unicore.")


def write_version_py():
    with open(os.path.join("unicore", "version.txt")) as f:
        version = f.read().strip()

    # write version info to unicore/version.py
    with open(os.path.join("unicore", "version.py"), "w") as f:
        f.write('__version__ = "{}"\n'.format(version))
    return version


version = write_version_py()


# ninja build does not work unless include_dirs are abs path
this_dir = os.path.dirname(os.path.abspath(__file__))
def get_cuda_bare_metal_version(cuda_dir):
    raw_output = subprocess.check_output([cuda_dir + "/bin/hipcc", "-V"], universal_newlines=True)
    output = raw_output.split()
    release_idx = output.index("release") + 1
    release = output[release_idx].split(".")
    bare_metal_major = release[0]
    bare_metal_minor = release[1][0]

    return raw_output, bare_metal_major, bare_metal_minor




if not torch.cuda.is_available():
    print('\nWarning: Torch did not find available GPUs on this system.\n',
          'If your intention is to cross-compile, this is not an error.\n'
          'By default, it will cross-compile for Volta (compute capability 7.0), Turing (compute capability 7.5),\n'
          'and, if the CUDA version is >= 11.0, Ampere (compute capability 8.0).\n'
          'If you wish to cross-compile for a single specific architecture,\n'
          'export TORCH_CUDA_ARCH_LIST="compute capability" before running setup.py.\n')
    if os.environ.get("TORCH_CUDA_ARCH_LIST", None) is None:
        _, bare_metal_major, _ = get_cuda_bare_metal_version(cpp_extension.CUDA_HOME)
        if int(bare_metal_major) == 11:
            os.environ["TORCH_CUDA_ARCH_LIST"] = "7.0;7.5;8.0"
        else:
            os.environ["TORCH_CUDA_ARCH_LIST"] = "7.0;7.5"

print("\n\ntorch.__version__  = {}\n\n".format(torch.__version__))
TORCH_MAJOR = int(torch.__version__.split('.')[0])
TORCH_MINOR = int(torch.__version__.split('.')[1])

if not (TORCH_MAJOR >= 1 and TORCH_MINOR >= 4):
      raise RuntimeError("Requires Pytorch 1.4 or newer.\n" +
                         "The latest stable release can be obtained from https://pytorch.org/")

cmdclass = {}
ext_modules = []

extras = {}


def get_cuda_bare_metal_version(cuda_dir):
    raw_output = subprocess.check_output([cuda_dir + "/bin/hipcc", "-V"], universal_newlines=True)
    output = raw_output.split()
    release_idx = output.index("release") + 1
    release = output[release_idx].split(".")
    bare_metal_major = release[0]
    bare_metal_minor = release[1][0]

    return raw_output, bare_metal_major, bare_metal_minor

def check_cuda_torch_binary_vs_bare_metal(cuda_dir):
    raw_output, bare_metal_major, bare_metal_minor = get_cuda_bare_metal_version(cuda_dir)
    torch_binary_major = torch.version.cuda.split(".")[0]
    torch_binary_minor = torch.version.cuda.split(".")[1]

    print("\nCompiling cuda extensions with")
    print(raw_output + "from " + cuda_dir + "/bin\n")

    if (bare_metal_major != torch_binary_major) or (bare_metal_minor != torch_binary_minor):
        raise RuntimeError("Cuda extensions are being compiled with a version of Cuda that does " +
                           "not match the version used to compile Pytorch binaries.  " +
                           "Pytorch binaries were compiled with Cuda {}.\n".format(torch.version.cuda))



cmdclass['build_ext'] = BuildExtension

if torch.utils.cpp_extension.CUDA_HOME is None:
    raise RuntimeError("Nvcc was not found.  Are you sure your environment has hipcc available?  If you're installing within a container from https://hub.docker.com/r/pytorch/pytorch, only images whose names contain 'devel' will provide hipcc.")


#check_cuda_torch_binary_vs_bare_metal(torch.utils.cpp_extension.CUDA_HOME)

generator_flag = []
#generator_flag += [('HIP_DIFF',None)]

torch_dir = torch.__path__[0]
if os.path.exists(os.path.join(torch_dir, 'include', 'ATen', 'CUDAGenerator.h')):
    generator_flag = ['-DOLD_GENERATOR']

ext_modules.append(
CUDAExtension(name='unicore_fused_rounding',
                sources=['csrc/rounding/interface_hip.cpp',
                        'csrc/rounding/fp32_to_bf16.hip'],
                include_dirs=[os.path.join(this_dir, 'csrc')],
                extra_compile_args={'cxx': ['-O3',] + generator_flag,
                                        'hipcc':['-O3', '--use_fast_math',
                                                '-gencode', 'arch=gfx906',
                                                '-gencode', 'arch=gfx906',
                                               # '-U__CUDA_NO_HALF_OPERATORS__',
                                               # '-U__CUDA_NO_BFLOAT16_OPERATORS__',
                                               # '-U__CUDA_NO_HALF_CONVERSIONS__',
                                               # '-U__CUDA_NO_BFLOAT16_CONVERSIONS__',
                                                '--expt-relaxed-constexpr',
                                                '--expt-extended-lambda'] + generator_flag}))

ext_modules.append(
    CUDAExtension(name='unicore_fused_multi_tensor',
                    sources=['csrc/multi_tensor/interface.cpp',
#                            'csrc/multi_tensor/multi_tensor_l2norm_kernel.cu'],
                    'csrc/multi_tensor/multi_tensor_l2norm_kernel.hip'],
                    include_dirs=[os.path.join(this_dir, 'csrc')],
                    extra_compile_args={'cxx': ['-O3'],
                                        'hipcc':['-O3', '--use_fast_math',
                                                '-gencode', 'arch=gfx906',
                                                '-gencode', 'arch=gfx906',
                                               # '-U__CUDA_NO_HALF_OPERATORS__',
                                               # '-U__CUDA_NO_BFLOAT16_OPERATORS__',
                                               # '-U__CUDA_NO_HALF_CONVERSIONS__',
                                               # '-U__CUDA_NO_BFLOAT16_CONVERSIONS__',
                                                '--expt-relaxed-constexpr',
                                                '--expt-extended-lambda']
                                        }))


ext_modules.append(
    CUDAExtension(name='unicore_fused_adam',
                    sources=['csrc/adam/interface.cpp',
                            'csrc/adam/adam_kernel.hip'],
                    include_dirs=[os.path.join(this_dir, 'csrc')],
                    extra_compile_args={'cxx': ['-O3'],
                                        'hipcc':['-O3', '--use_fast_math']}))

ext_modules.append(
    CUDAExtension(name='unicore_fused_softmax_dropout',
                    sources=['csrc/softmax_dropout/interface_hip.cpp',
                            'csrc/softmax_dropout/softmax_dropout_kernel.hip'],
                    include_dirs=[os.path.join(this_dir, 'csrc')],
                    extra_compile_args={'cxx': ['-O3',] + generator_flag,
                                        'hipcc':['-O3', '--use_fast_math',
                                                '-gencode', 'arch=gfx906',
                                                '-gencode', 'arch=gfx906',
                                                #'-U__CUDA_NO_HALF_OPERATORS__',
                                                #'-U__CUDA_NO_BFLOAT16_OPERATORS__',
                                                #'-U__CUDA_NO_HALF_CONVERSIONS__',
                                                #'-U__CUDA_NO_BFLOAT16_CONVERSIONS__',
                                                '--expt-relaxed-constexpr',
                                                '--expt-extended-lambda'] + generator_flag}))


ext_modules.append(
    CUDAExtension(name='unicore_fused_layernorm',
                    sources=['csrc/layernorm/interface.cpp',
                            'csrc/layernorm/layernorm.hip'],
                    include_dirs=[os.path.join(this_dir, 'csrc')],
                    extra_compile_args={'cxx': ['-O3',] + generator_flag,
                                        'hipcc':['-O3', '--use_fast_math',
                                                '-gencode', 'arch=gfx906',
                                                '-gencode', 'arch=gfx906',
                                                #'-U__CUDA_NO_HALF_OPERATORS__',
                                                #'-U__CUDA_NO_BFLOAT16_OPERATORS__',
                                                #'-U__CUDA_NO_HALF_CONVERSIONS__',
                                                #'-U__CUDA_NO_BFLOAT16_CONVERSIONS__',
                                                '--expt-relaxed-constexpr',
                                                '--expt-extended-lambda'] + generator_flag}))


ext_modules.append(
    CUDAExtension(name='unicore_fused_layernorm_backward_gamma_beta',
                    sources=['csrc/layernorm/interface_gamma_beta.cpp',
                            'csrc/layernorm/layernorm_backward.hip'],
                    include_dirs=[os.path.join(this_dir, 'csrc')],
                    extra_compile_args={'cxx': ['-O3',] + generator_flag,
                                        'hipcc':['-O3', '--use_fast_math', '-maxrregcount=50',
                                                '-gencode', 'arch=gfx906',
                                                '-gencode', 'arch=gfx906',
                                                #'-U__CUDA_NO_HALF_OPERATORS__',
                                                #'-U__CUDA_NO_BFLOAT16_OPERATORS__',
                                                #'-U__CUDA_NO_HALF_CONVERSIONS__',
                                                #'-U__CUDA_NO_BFLOAT16_CONVERSIONS__',
                                                '--expt-relaxed-constexpr',
                                                '--expt-extended-lambda'] + generator_flag}))


setup(
    name="unicore",
    version=version,
    description="DP Technology's Core AI Framework",
    url="https://github.com/dptech-corp/unicore",
    classifiers=[
        "Intended Audience :: Science/Research",
        "License :: OSI Approved :: MIT License",
        "Programming Language :: Python :: 3.7",
        "Programming Language :: Python :: 3.8",
        "Programming Language :: Python :: 3.9",
        "Programming Language :: Python :: 3.10",
        "Topic :: Scientific/Engineering :: Artificial Intelligence",
    ],
    setup_requires=[
        "setuptools>=18.0",
    ],
    install_requires=[
        'numpy; python_version>="3.7"',
        "lmdb",
        #"torch>=1.10.0",
        "tqdm",
        "ml_collections",
        "scipy",
        "tensorboardX",
        "tokenizers",
    ],
    packages=find_packages(
        exclude=[
            'build',
            'csrc',
            "examples",
            "examples.*",
            "scripts",
            "scripts.*",
            "tests",
            "tests.*",
        ]
    ),
    ext_modules=ext_modules,
    cmdclass=cmdclass,
    extras_require=extras,
    entry_points={
        "console_scripts": [
            "unicore-train = unicore_cli.train:cli_main",
        ],
    },
    zip_safe=False,
)

