| /external/tensorflow/tensorflow/python/ops/distributions/ |
| D | categorical.py | 317 nn_ops.log_softmax(self.logits) * self.probs, axis=-1)
342 delta_log_probs1 = (nn_ops.log_softmax(a.logits) -
343 nn_ops.log_softmax(b.logits))
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| D | multinomial.py | 281 return math_ops.reduce_sum(counts * nn_ops.log_softmax(self.logits), -1)
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| /external/tensorflow/tensorflow/python/keras/ |
| D | activations.py | 515 log_softmax = nn.log_softmax variable
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| /external/tensorflow/tensorflow/dtensor/mlir/expansions/ |
| D | softmax_spmd_expander.cc | 159 auto log_softmax = builder.create<mlir::TF::SubOp>( in ComputeLogSoftmax() local
161 return log_softmax.getResult(); in ComputeLogSoftmax()
169 bool log_softmax) { in ComputeShardedSoftmax() argument
177 if (log_softmax) { in ComputeShardedSoftmax()
579 const mlir::Value log_softmax = in ExpandOp() local
599 features_zero, log_softmax) in ExpandOp()
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| /external/tensorflow/tensorflow/lite/testing/op_tests/ |
| D | log_softmax.py | 38 out = tf.nn.log_softmax(input_tensor)
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| /external/tensorflow/tensorflow/python/kernel_tests/nn_ops/ |
| D | softmax_op_test.py | 71 tf_softmax = nn_ops.log_softmax(np_features, axis=dim, name=name)
122 tf_log_softmax = nn_ops.log_softmax(features)
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| /external/tensorflow/tensorflow/python/ops/ragged/ |
| D | ragged_tensor_test_ops.py | 80 nn_ops.log_softmax,
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| /external/tensorflow/tensorflow/lite/kernels/internal/ |
| D | BUILD | 555 "reference/log_softmax.h",
587 "reference/integer_ops/log_softmax.h",
659 "reference/log_softmax.h",
|
| /external/tensorflow/tensorflow/compiler/mlir/lite/tests/ |
| D | get-arithmetic-count.mlir | 86 %0 = "tfl.log_softmax"(%arg0) : (tensor<10x10xf32>) -> tensor<10x10xf32>
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| D | legalize-tf.mlir | 255 func.func @log_softmax(%arg0: tensor<8x16xf32>) -> tensor<8x16xf32> {
258 // CHECK-LABEL: log_softmax
259 // CHECK: "tfl.log_softmax"(%arg0) : (tensor<8x16xf32>) -> tensor<8x16xf32>
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| /external/tensorflow/tensorflow/python/kernel_tests/distributions/ |
| D | categorical_test.py | 339 log_probabilities = nn_ops.log_softmax(logits)
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| /external/tensorflow/tensorflow/lite/testing/ |
| D | generate_examples_lib.py | 108 from tensorflow.lite.testing.op_tests.log_softmax import make_log_softmax_tests
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| D | build_def.bzl | 88 "log_softmax",
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| /external/tensorflow/tensorflow/tools/api/golden/v2/ |
| D | tensorflow.nn.pbtxt | 220 name: "log_softmax"
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| D | tensorflow.math.pbtxt | 264 name: "log_softmax"
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| /external/tensorflow/tensorflow/python/ops/ |
| D | nn_ops.py | 3918 def log_softmax(logits, axis=None, name=None, dim=None): function
3943 return _wrap_2d_function(logits, gen_nn_ops.log_softmax, axis, name)
3971 return _wrap_2d_function(logits, gen_nn_ops.log_softmax, axis, name)
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| D | ctc_ops.py | 702 ilabel_log_probs = nn_ops.log_softmax(logits)
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| D | nn_grad.py | 534 …return grad, _BroadcastMul(grad_loss, -nn_ops.log_softmax(logits)) # pylint: disable=invalid-unar…
|
| /external/tensorflow/tensorflow/python/ops/numpy_ops/g3doc/ |
| D | TensorFlow_NumPy_Text_Generation.ipynb | 804 …"We define the loss function from scratch, using `tf.nn.log_softmax`. (Our definition is the same …
819 " predictions = tf.nn.log_softmax(predictions)\n",
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| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.math.pbtxt | 264 name: "log_softmax"
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| D | tensorflow.nn.pbtxt | 256 name: "log_softmax"
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| /external/tensorflow/tensorflow/compiler/mlir/lite/transforms/ |
| D | optimize_patterns.td | 901 (ArgMinMaxOp (TFL_LogSoftmaxOp:$log_softmax $logits),
904 [(HasOneUse $log_softmax),
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| /external/tensorflow/tensorflow/python/ops/parallel_for/ |
| D | control_flow_ops_test.py | 767 return (nn.log_softmax(logits_i), nn.log_softmax(logits_i, axis=0),
768 nn.log_softmax(logits_i, axis=-1))
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| /external/tensorflow/tensorflow/compiler/tf2tensorrt/ |
| D | BUILD | 681 "convert/ops/log_softmax.cc",
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| /external/tensorflow/tensorflow/compiler/tests/ |
| D | unary_ops_test.py | 369 nn_ops.log_softmax,
|