"""
GPU inplace copy using direct CUDA memory copy.
Uses cuda_rt library similar to ACL's acl.rt.memcpy.
"""
import mindspore as ms
from mindspore import ops

try:
    from .cuda_rt import rt as cuda_rt
    from .cuda_rt import cudaMemcpyDeviceToDevice, CudaRTError
    _CUDA_RT_AVAILABLE = True
except ImportError:
    _CUDA_RT_AVAILABLE = False
    cuda_rt = None


def _get_tensor_device_ptr(tensor):
    """
    Get device pointer from MindSpore tensor.
    This is a helper function - actual implementation depends on MindSpore's internal API.
    """
    try:
        # Try different ways to get device pointer
        if hasattr(tensor, 'device_address'):
            return tensor.device_address
        if hasattr(tensor, '_device_address'):
            return tensor._device_address
        if hasattr(tensor, 'data_ptr'):
            return tensor.data_ptr()
        # Try to get from tensor's internal structure
        if hasattr(tensor, '_tensor'):
            t = tensor._tensor
            if hasattr(t, 'device_address'):
                return t.device_address
        return None
    except Exception:
        return None


def inplace_copy_gpu_memcpy(input, value):
    """
    Inplace copy using direct CUDA memory copy (similar to acl.rt.memcpy).
    
    Args:
        input: The input tensor to be modified in-place
        value: The value tensor to copy into input
        
    Returns:
        The input tensor (modified in-place)
    """
    if not _CUDA_RT_AVAILABLE:
        # Fallback to assign_value if CUDA RT not available
        input.assign_value(value)
        return input
    
    # Handle shape mismatch
    if value.shape != input.shape:
        value = ops.broadcast_to(value, input.shape)
    
    # Handle dtype mismatch
    if value.dtype != input.dtype:
        value = ops.cast(value, input.dtype)
    
    # Get device pointers
    input_ptr = _get_tensor_device_ptr(input)
    value_ptr = _get_tensor_device_ptr(value)
    
    # Validate pointers - must be non-None and non-zero
    if input_ptr is None or value_ptr is None:
        # Fallback to assign_value if we can't get device pointers
        input.assign_value(value)
        return input
    
    # Convert to int for validation
    try:
        input_ptr_int = int(input_ptr) if not isinstance(input_ptr, int) else input_ptr
        value_ptr_int = int(value_ptr) if not isinstance(value_ptr, int) else value_ptr
    except (TypeError, ValueError):
        # Invalid pointer type, fallback
        input.assign_value(value)
        return input
    
    # Check if pointers are valid (non-zero)
    if input_ptr_int == 0 or value_ptr_int == 0:
        # NULL pointers, fallback
        input.assign_value(value)
        return input
    
    # Calculate size in bytes
    try:
        input_size = input.nbytes if hasattr(input, 'nbytes') else input.size * input.itemsize
        value_size = value.nbytes if hasattr(value, 'nbytes') else value.size * value.itemsize
        copy_size = min(input_size, value_size)
        
        # Validate copy size
        if copy_size <= 0:
            input.assign_value(value)
            return input
    except (AttributeError, TypeError):
        # Can't calculate size, fallback
        input.assign_value(value)
        return input
    
    try:
        # Use cuda_rt.memcpy for device-to-device copy
        cuda_rt.memcpy(input_ptr_int, value_ptr_int, copy_size, cudaMemcpyDeviceToDevice)
        # Synchronize to ensure copy is complete
        cuda_rt.synchronize()
    except (CudaRTError, Exception) as e:
        # Fallback to assign_value if direct memcpy fails
        # This handles cases where pointers might not be valid device pointers
        # or CUDA operations fail for any reason
        input.assign_value(value)
    
    return input


def inplace_copy_gpu_simple(input, value):
    """
    Simple GPU inplace copy using MindSpore's built-in operations.
    This uses GPU memory copy internally when tensors are on GPU.
    
    Args:
        input: The input tensor to be modified in-place
        value: The value tensor to copy into input
        
    Returns:
        The input tensor (modified in-place)
    """
    # Handle shape mismatch
    if value.shape != input.shape:
        value = ops.broadcast_to(value, input.shape)
    
    # Handle dtype mismatch
    if value.dtype != input.dtype:
        value = ops.cast(value, input.dtype)
    
    # Use assign_value which performs GPU memory copy for GPU tensors
    input.assign_value(value)
    
    return input

