import os
import torch
import megatron.core.parallel_state as ps
from datetime import timedelta
import pytest

#TODO: Maybe get these values frome environment variables 
rank = torch.cuda.current_device()
world_size = 1 #torch.cuda.device_count()
tensor_model_parallel_size = 1
pipeline_model_parallel_size = 1
virtual_pipeline_model_parallel_size = None
pipeline_model_parallel_split_rank = None

def initialize_distributed():
    rank = torch.cuda.current_device()   
    print(f'Initializing torch.distributed with rank: {rank}, world_size: {world_size}')
    torch.cuda.set_device(rank % torch.cuda.device_count())
    init_method = 'tcp://'
    master_ip = os.getenv('MASTER_ADDR', 'localhost')
    master_port = os.getenv('MASTER_PORT', '6000')
    init_method += master_ip + ':' + master_port
    torch.distributed.init_process_group(backend='nccl', world_size=world_size, rank=rank, init_method=init_method, timeout=timedelta(seconds=10))

def test_initialize_model_parallel():
    with pytest.raises(AssertionError):
        assert(ps.initialize_model_parallel())
    initialize_distributed()
    with pytest.raises(RuntimeError):
        assert(ps.initialize_model_parallel(tensor_model_parallel_size=2))
    with pytest.raises(RuntimeError):
        assert(ps.initialize_model_parallel(pipeline_model_parallel_size=2))
    ps.initialize_model_parallel()

def test_other_initializations():
    assert(ps.model_parallel_is_initialized())
    assert(ps.get_model_parallel_group() is not None)
    assert(ps.get_tensor_model_parallel_group() is not None)
    assert(ps.get_pipeline_model_parallel_group() is not None)
    assert(ps.get_data_parallel_group() is not None)  
    assert(ps.get_embedding_group() is not None)  
    assert(ps.get_position_embedding_group() is not None)
    #TODO : Should change some of these test below to actually test code
    assert(ps.get_pipeline_model_parallel_first_rank() == 0)
    assert(ps.get_data_parallel_src_rank() == 0)
    assert(ps.get_pipeline_model_parallel_next_rank() == 0)
    assert(ps.get_pipeline_model_parallel_prev_rank() == 0)
    assert(ps.get_data_parallel_world_size() == world_size)
    assert(ps.get_data_parallel_rank() == 0)

def test_tensor_model_parellel_world_size():
    ps.set_tensor_model_parallel_world_size(world_size)
    assert(ps.get_tensor_model_parallel_world_size() == world_size)
    ps.set_tensor_model_parallel_world_size(None)
    assert(ps.get_tensor_model_parallel_world_size() == world_size)

def test_pipeline_model_parallel_world_size():
    ps.set_pipeline_model_parallel_world_size(world_size)
    assert(ps.get_pipeline_model_parallel_world_size() == world_size)
    ps.set_pipeline_model_parallel_world_size(None)
    assert(ps.get_pipeline_model_parallel_world_size() == world_size)

def test_tensor_model_parallel_rank():
    ps.set_tensor_model_parallel_rank(rank)
    assert(ps.get_tensor_model_parallel_rank() == rank)
    ps.set_tensor_model_parallel_rank(None)
    assert(ps.get_tensor_model_parallel_rank() == rank)    

def test_tensor_model_parallel_rank():
    ps.set_pipeline_model_parallel_rank(rank)
    assert(ps.get_pipeline_model_parallel_rank() == rank)
    ps.set_pipeline_model_parallel_rank(None)
    assert(ps.get_pipeline_model_parallel_rank() == rank)

def test_is_pipeline_first_stage():
    assert(ps.is_pipeline_first_stage(ignore_virtual=True))
    assert(ps.is_pipeline_first_stage())

def test_is_pipeline_last_stage():
    assert(
        ps.is_pipeline_last_stage(ignore_virtual=True) == (ps.get_pipeline_model_parallel_rank() == world_size-1)
        )
    assert(
        ps.is_pipeline_last_stage() == (ps.get_pipeline_model_parallel_rank() == world_size-1)
        )

def test_is_rank_in_embedding_group():
    assert(ps.is_rank_in_embedding_group(ignore_virtual=True) == (rank in ps._EMBEDDING_GLOBAL_RANKS))
    if rank in ps._EMBEDDING_GLOBAL_RANKS:
        assert(ps.is_rank_in_embedding_group() == ps.is_pipeline_first_stage())
    elif rank == _EMBEDDING_GLOBAL_RANKS[-1]:
        assert(ps.is_rank_in_embedding_group() == ps.is_pipeline_last_stage())
    else:
        assert(ps.is_rank_in_embedding_group())

def test_is_rank_in_position_embedding_group():
    assert(ps.is_rank_in_position_embedding_group() == (rank in ps._POSITION_EMBEDDING_GLOBAL_RANKS))

def test_is_pipeline_stage_before_split():
    if world_size == 1:
        assert(ps.is_pipeline_stage_before_split())
    # TODO: Changes here for more than one world size
    assert(ps.is_pipeline_stage_before_split())

def test_is_pipeline_stage_after_split():
    if world_size == 1:
        assert(ps.is_pipeline_stage_after_split())
    # TODO: Changes here for more than one world size
    assert(ps.is_pipeline_stage_before_split())   

def test_is_pipeline_stage_at_split():
    assert(
        ps.is_pipeline_stage_at_split() == 
        (ps.is_pipeline_stage_before_split(rank) and ps.is_pipeline_stage_after_split(rank+1))
        )

def test_virtual_pipeline_model_parallel_rank():
    ps.set_virtual_pipeline_model_parallel_rank(rank)
    assert(ps.get_virtual_pipeline_model_parallel_rank() == rank)

def test_virtual_pipeline_model_parallel_rank():
    ps.set_virtual_pipeline_model_parallel_rank(rank)
    assert(ps.get_virtual_pipeline_model_parallel_rank() == rank)

def test_get_virtual_pipeline_model_parallel_world_size():
    assert(ps.get_virtual_pipeline_model_parallel_world_size() == virtual_pipeline_model_parallel_size)

def test_get_tensor_model_parallel_src_rank():
    assert(ps.get_tensor_model_parallel_src_rank() == ((rank // world_size) * world_size))

def global_memory_buffer():
    ps._set_global_memory_buffer()
    assert(ps.get_global_memory_buffer() is not None)