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e2fdceb3c8
We need this as we will update a new Jaxlib with `shape` returning a tuple, and as the submission process in in 2 steps, we need this before updating xla.cc
70 lines
2.8 KiB
Python
70 lines
2.8 KiB
Python
# Copyright 2020 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# https://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from jax import core
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from jax import lazy
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from jax.interpreters import xla
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import jax.lib
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from jax.lib import xla_client
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from jax.lib import xla_bridge
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def to_dlpack(x: xla.DeviceArray, take_ownership: bool = False):
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"""Returns a DLPack tensor that encapsulates a DeviceArray `x`.
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Takes ownership of the contents of `x`; leaves `x` in an invalid/deleted
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state.
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Args:
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x: a `DeviceArray`, on either CPU or GPU.
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take_ownership: If ``True``, JAX hands ownership of the buffer to DLPack,
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and the consumer is free to mutate the buffer; the JAX buffer acts as if
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it were deleted. If ``False``, JAX retains ownership of the buffer; it is
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undefined behavior if the DLPack consumer writes to a buffer that JAX
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owns.
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"""
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if not isinstance(x, xla.DeviceArray):
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raise TypeError("Argument to to_dlpack must be a DeviceArray, got {}"
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.format(type(x)))
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buf = xla._force(x).device_buffer
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if jax.lib.version >= (0, 1, 57):
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return xla_client._xla.buffer_to_dlpack_managed_tensor(
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buf, take_ownership=take_ownership)
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else:
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# Jaxlibs before 0.1.57 always take ownership.
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if not take_ownership:
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raise ValueError(
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"to_dlpack with take_ownership=False requires jaxlib >= 0.1.57")
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return xla_client._xla.buffer_to_dlpack_managed_tensor(buf)
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def from_dlpack(dlpack, backend=None):
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"""Returns a `DeviceArray` representation of a DLPack tensor `dlpack`.
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The returned `DeviceArray` shares memory with `dlpack`.
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Args:
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dlpack: a DLPack tensor, on either CPU or GPU.
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backend: experimental, optional: the platform on which `dlpack` lives.
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"""
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# TODO(phawkins): ideally the user wouldn't need to provide a backend and we
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# would be able to figure it out from the DLPack.
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backend = backend or xla_bridge.get_backend()
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client = getattr(backend, "client", backend)
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buf = xla_client._xla.dlpack_managed_tensor_to_buffer(dlpack, client)
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# TODO(jblespiau): We can simply use buf.xla_shape() when version 0.1.58 is
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# the default.
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xla_shape = getattr(buf, "xla_shape", buf.shape)()
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assert not xla_shape.is_tuple()
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aval = core.ShapedArray(xla_shape.dimensions(), xla_shape.numpy_dtype())
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return xla.make_device_array(aval, buf.device(), lazy.array(aval.shape), buf) # pytype: disable=attribute-error
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