def _ComputeSampledLogitsTF(self,
weights,
biases,
hidden_acts,
labels,
num_sampled,
num_classes,
num_true,
sampled_vals,
subtract_log_q,
remove_accidental_hits,
name="sampled_loss_TF"):
# Should be called from within a `with test_session():` block
weights_tf = constant_op.constant(weights)
biases_tf = constant_op.constant(biases)
hidden_acts_tf = constant_op.constant(hidden_acts,
shape=(self._batch_size,
self._dim))
labels_tf = constant_op.constant(labels,
dtype=types.int64,
shape=(self._batch_size, num_true))
pred_logits_tf, pred_labels_tf = nn._compute_sampled_logits(
weights_tf,
biases_tf,
hidden_acts_tf,
labels_tf,
num_sampled,
num_classes,
num_true,
sampled_vals,
subtract_log_q=subtract_log_q,
remove_accidental_hits=remove_accidental_hits,
name=name)
return pred_logits_tf, pred_labels_tf
def sampled_sigmoid_loss(weights,
biases,
inputs,
labels,
num_sampled,
num_classes,
num_true=2,
sampled_values=None,
remove_accidental_hits=True,
partition_strategy="mod",
name="sampled_softmax_loss"):
logits, labels = _compute_sampled_logits(
weights,
biases,
inputs,
labels,
num_sampled,
num_classes,
num_true=num_true,
sampled_values=sampled_values,
subtract_log_q=True,
remove_accidental_hits=remove_accidental_hits,
partition_strategy=partition_strategy,
name=name)
sampled_losses = nn_ops.sigmoid_cross_entropy_with_logits(logits, labels)
return sampled_losses
def _ComputeSampledLogitsTF(self, weights, biases, hidden_acts, labels,
num_sampled, num_classes, num_true, sampled_vals,
subtract_log_q, remove_accidental_hits,
name="sampled_loss_TF"):
# Should be called from within a `with test_session():` block
weights_tf = constant_op.constant(weights)
biases_tf = constant_op.constant(biases)
hidden_acts_tf = constant_op.constant(hidden_acts,
shape=(self._batch_size, self._dim))
labels_tf = constant_op.constant(labels, dtype=types.int64,
shape=(self._batch_size, num_true))
pred_logits_tf, pred_labels_tf = nn._compute_sampled_logits(
weights_tf, biases_tf, hidden_acts_tf, labels_tf, num_sampled,
num_classes, num_true, sampled_vals,
subtract_log_q=subtract_log_q,
remove_accidental_hits=remove_accidental_hits,
name=name)
return pred_logits_tf, pred_labels_tf