Python detectron.utils.c2.CudaDevice() Examples

The following are 6 code examples of detectron.utils.c2.CudaDevice(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module detectron.utils.c2 , or try the search function .
Example #1
Source File: loader.py    From KL-Loss with Apache License 2.0 6 votes vote down vote up 
def enqueue_blobs(self, gpu_id, blob_names, blobs):
        """Put a mini-batch on a BlobsQueue."""
        assert len(blob_names) == len(blobs)
        t = time.time()
        dev = c2_utils.CudaDevice(gpu_id)
        queue_name = 'gpu_{}/{}'.format(gpu_id, self._blobs_queue_name)
        blob_names = ['gpu_{}/{}'.format(gpu_id, b) for b in blob_names]
        for (blob_name, blob) in zip(blob_names, blobs):
            workspace.FeedBlob(blob_name, blob, device_option=dev)
        logger.debug(
            'enqueue_blobs {}: workspace.FeedBlob: {}'.
            format(gpu_id, time.time() - t)
        )
        t = time.time()
        op = core.CreateOperator(
            'SafeEnqueueBlobs', [queue_name] + blob_names,
            blob_names + [queue_name + '_enqueue_status'],
            device_option=dev
        )
        workspace.RunOperatorOnce(op)
        logger.debug(
            'enqueue_blobs {}: workspace.RunOperatorOnce: {}'.
            format(gpu_id, time.time() - t)
        )
Example #2
Source File: loader.py    From Clustered-Object-Detection-in-Aerial-Image with Apache License 2.0 6 votes vote down vote up 
def enqueue_blobs(self, gpu_id, blob_names, blobs):
        """Put a mini-batch on a BlobsQueue."""
        assert len(blob_names) == len(blobs)
        t = time.time()
        dev = c2_utils.CudaDevice(gpu_id)
        queue_name = 'gpu_{}/{}'.format(gpu_id, self._blobs_queue_name)
        blob_names = ['gpu_{}/{}'.format(gpu_id, b) for b in blob_names]
        for (blob_name, blob) in zip(blob_names, blobs):
            workspace.FeedBlob(blob_name, blob, device_option=dev)
        logger.debug(
            'enqueue_blobs {}: workspace.FeedBlob: {}'.
            format(gpu_id, time.time() - t)
        )
        t = time.time()
        op = core.CreateOperator(
            'SafeEnqueueBlobs', [queue_name] + blob_names,
            blob_names + [queue_name + '_enqueue_status'],
            device_option=dev
        )
        workspace.RunOperatorOnce(op)
        logger.debug(
            'enqueue_blobs {}: workspace.RunOperatorOnce: {}'.
            format(gpu_id, time.time() - t)
        )
Example #3
Source File: loader.py    From Detectron-Cascade-RCNN with Apache License 2.0 6 votes vote down vote up 
def enqueue_blobs(self, gpu_id, blob_names, blobs):
        """Put a mini-batch on a BlobsQueue."""
        assert len(blob_names) == len(blobs)
        t = time.time()
        dev = c2_utils.CudaDevice(gpu_id)
        queue_name = 'gpu_{}/{}'.format(gpu_id, self._blobs_queue_name)
        blob_names = ['gpu_{}/{}'.format(gpu_id, b) for b in blob_names]
        for (blob_name, blob) in zip(blob_names, blobs):
            workspace.FeedBlob(blob_name, blob, device_option=dev)
        logger.debug(
            'enqueue_blobs {}: workspace.FeedBlob: {}'.
            format(gpu_id, time.time() - t)
        )
        t = time.time()
        op = core.CreateOperator(
            'SafeEnqueueBlobs', [queue_name] + blob_names,
            blob_names + [queue_name + '_enqueue_status'],
            device_option=dev
        )
        workspace.RunOperatorOnce(op)
        logger.debug(
            'enqueue_blobs {}: workspace.RunOperatorOnce: {}'.
            format(gpu_id, time.time() - t)
        )
Example #4
Source File: loader.py    From Detectron with Apache License 2.0 6 votes vote down vote up 
def enqueue_blobs(self, gpu_id, blob_names, blobs):
        """Put a mini-batch on a BlobsQueue."""
        assert len(blob_names) == len(blobs)
        t = time.time()
        dev = c2_utils.CudaDevice(gpu_id)
        queue_name = 'gpu_{}/{}'.format(gpu_id, self._blobs_queue_name)
        blob_names = ['gpu_{}/{}'.format(gpu_id, b) for b in blob_names]
        for (blob_name, blob) in zip(blob_names, blobs):
            workspace.FeedBlob(blob_name, blob, device_option=dev)
        logger.debug(
            'enqueue_blobs {}: workspace.FeedBlob: {}'.
            format(gpu_id, time.time() - t)
        )
        t = time.time()
        op = core.CreateOperator(
            'SafeEnqueueBlobs', [queue_name] + blob_names,
            blob_names + [queue_name + '_enqueue_status'],
            device_option=dev
        )
        workspace.RunOperatorOnce(op)
        logger.debug(
            'enqueue_blobs {}: workspace.RunOperatorOnce: {}'.
            format(gpu_id, time.time() - t)
        )
Example #5
Source File: loader.py    From Detectron-DA-Faster-RCNN with Apache License 2.0 6 votes vote down vote up 
def enqueue_blobs(self, gpu_id, blob_names, blobs):
        """Put a mini-batch on a BlobsQueue."""
        assert len(blob_names) == len(blobs)
        t = time.time()
        dev = c2_utils.CudaDevice(gpu_id)
        queue_name = 'gpu_{}/{}'.format(gpu_id, self._blobs_queue_name)
        blob_names = ['gpu_{}/{}'.format(gpu_id, b) for b in blob_names]
        for (blob_name, blob) in zip(blob_names, blobs):
            workspace.FeedBlob(blob_name, blob, device_option=dev)
        logger.debug(
            'enqueue_blobs {}: workspace.FeedBlob: {}'.
            format(gpu_id, time.time() - t)
        )
        t = time.time()
        op = core.CreateOperator(
            'SafeEnqueueBlobs', [queue_name] + blob_names,
            blob_names + [queue_name + '_enqueue_status'],
            device_option=dev
        )
        workspace.RunOperatorOnce(op)
        logger.debug(
            'enqueue_blobs {}: workspace.RunOperatorOnce: {}'.
            format(gpu_id, time.time() - t)
        )
Example #6
Source File: loader.py    From CBNet with Apache License 2.0 6 votes vote down vote up 
def enqueue_blobs(self, gpu_id, blob_names, blobs):
        """Put a mini-batch on a BlobsQueue."""
        assert len(blob_names) == len(blobs)
        t = time.time()
        dev = c2_utils.CudaDevice(gpu_id)
        queue_name = 'gpu_{}/{}'.format(gpu_id, self._blobs_queue_name)
        blob_names = ['gpu_{}/{}'.format(gpu_id, b) for b in blob_names]
        for (blob_name, blob) in zip(blob_names, blobs):
            workspace.FeedBlob(blob_name, blob, device_option=dev)
        logger.debug(
            'enqueue_blobs {}: workspace.FeedBlob: {}'.
            format(gpu_id, time.time() - t)
        )
        t = time.time()
        op = core.CreateOperator(
            'SafeEnqueueBlobs', [queue_name] + blob_names,
            blob_names + [queue_name + '_enqueue_status'],
            device_option=dev
        )
        workspace.RunOperatorOnce(op)
        logger.debug(
            'enqueue_blobs {}: workspace.RunOperatorOnce: {}'.
            format(gpu_id, time.time() - t)
        )