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60 lines
1.9 KiB
Python
60 lines
1.9 KiB
Python
# Copyright 2019 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 __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from jax.abstract_arrays import ShapedArray
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from jax.core import Primitive
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from jax.interpreters import xla
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from ..interpreters import ad
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from ..interpreters import batching
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def fft(x, fft_type, fft_lengths=None):
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if fft_lengths is None:
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fft_lengths = x.shape
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elif len(fft_lengths) == 0:
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# XLA FFT doesn't support 0-rank.
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return x
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else:
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fft_lengths = tuple(fft_lengths)
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return fft_p.bind(x, fft_type=fft_type, fft_lengths=fft_lengths)
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def fft_impl(x, fft_type, fft_lengths):
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return xla.apply_primitive(fft_p, x, fft_type=fft_type, fft_lengths=fft_lengths)
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def fft_abstract_eval(x, fft_type, fft_lengths):
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return ShapedArray(x.shape, x.dtype)
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def fft_translation_rule(c, x, fft_type, fft_lengths):
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return c.Fft(x, fft_type, fft_lengths)
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def fft_transpose_rule(t, fft_type, fft_lengths):
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return fft(t, fft_type, fft_lengths),
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def fft_batching_rule(batched_args, batch_dims, fft_type, fft_lengths):
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x, = batched_args
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bd, = batch_dims
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x = batching.moveaxis(x, bd, 0)
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return fft(x, fft_type, fft_lengths), 0
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fft_p = Primitive('fft')
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fft_p.def_impl(fft_impl)
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fft_p.def_abstract_eval(fft_abstract_eval)
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xla.translations[fft_p] = fft_translation_rule
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ad.deflinear(fft_p, fft_transpose_rule)
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batching.primitive_batchers[fft_p] = fft_batching_rule
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