Searched refs:primals (Results 1 – 4 of 4) sorted by relevance
| /external/tensorflow/tensorflow/python/keras/integration_test/ |
| D | forwardprop_test.py | 27 def _jvp(f, primals, tangents): argument
29 with tf.autodiff.ForwardAccumulator(primals, tangents) as acc:
30 primals_out = f(*primals)
35 def _jacfwd(f, primals): argument
38 flat_primals = tf.nest.flatten(primals)
50 _jvp(f, primals, tf.nest.pack_sequence_as(primals,
54 return tf.nest.pack_sequence_as(primals, jac_flat)
72 def _hvp(f, primals, tangents): argument
74 with tf.autodiff.ForwardAccumulator(primals, tangents) as acc:
76 tape.watch(primals)
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| /external/tensorflow/tensorflow/python/eager/ |
| D | forwardprop.py | 332 def __init__(self, primals, tangents): argument
357 for primal in nest.flatten(primals):
364 self._watch(primals, tangents)
386 def _watch(self, primals, tangents): argument
415 nest.map_structure(_watch, primals, tangents, expand_composites=True)
417 def jvp(self, primals, unconnected_gradients=UnconnectedGradients.NONE): argument
450 return nest.map_structure(_fetch_jvp, primals)
453 def _batch_accumulator(cls, primals, tangents): argument
465 acc = super(ForwardAccumulator, cls).__new__(cls, primals, tangents)
469 for primal, tangent in zip(nest.flatten(primals), nest.flatten(tangents)):
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| D | forwardprop_test.py | 59 def _jvp(f, primals, tangents): argument
61 with forwardprop.ForwardAccumulator(primals, tangents) as acc:
62 primals_out = f(*primals)
67 def _jacfwd(f, primals): argument
70 flat_primals = nest.flatten(primals)
83 _jvp(f, primals, nest.pack_sequence_as(primals,
87 return nest.pack_sequence_as(primals, jac_flat)
97 def _jvp_batch_matmul(f, primals, tangent_batch): argument
99 jac_fwd = _jacfwd(f, primals)
132 primals=[params[argnums]], tangents=param_mask) as acc:
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| /external/tensorflow/tensorflow/tools/api/golden/v2/ |
| D | tensorflow.autodiff.-forward-accumulator.pbtxt | 7 … argspec: "args=[\'self\', \'primals\', \'tangents\'], varargs=None, keywords=None, defaults=None"
11 …argspec: "args=[\'self\', \'primals\', \'unconnected_gradients\'], varargs=None, keywords=None, de…
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