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[tfdbg2] A few fixes and improvements to example debug_mnist_v2 

1. Change the default `--dump_tensor_debug_mode` flag value to
   `FULL_HEALTH`, a mode more suitable for numerical instability
   debugging for the particular bug in this example than the previous
   default value `NO_TENSOR`.
2. Change the default `--dump_circular_buffer_size` value to -1, to
   accommodate the possibility of longer runs where user would
   want to see the debug data in its entirety.
3. Rename a few weight variables. They were previously named in a
   confusing way.
4. Change "logits" to "probs", as they are generated by a `softmax`
   operation and hence are more accurately described as probability
   scores.

PiperOrigin-RevId: 316473164
Change-Id: I4eb13f9581a4d4e550b3b3a5cd132eeffc7dd043
This commit is contained in:
Shanqing Cai 2020-06-15 08:47:31 -07:00 committed by TensorFlower Gardener
parent 1a0909a9f4
commit 06b1b45e42
1 changed files with 23 additions and 11 deletions
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34
tensorflow/python/debug/examples/v2/debug_mnist_v2.py
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@ -98,16 +98,18 @@ def parse_args():
parser.add_argument( parser.add_argument(
"--dump_tensor_debug_mode", "--dump_tensor_debug_mode",
type=str, type=str,
default="NO_TENSOR", default="FULL_HEALTH",
help="Mode for dumping tensor values. Options: NO_TENSOR, CURT_HEALTH, " help="Mode for dumping tensor values. Options: NO_TENSOR, CURT_HEALTH, "
"CONCISE_HEALTH, SHAPE, FULL_TENSOR. This is relevant only when " "CONCISE_HEALTH, SHAPE, FULL_HEALTH. This is relevant only when "
"--dump_dir is set.") "--dump_dir is set.")
# TODO(cais): Add more tensor debug mode strings once they are supported. # TODO(cais): Add more tensor debug mode strings once they are supported.
parser.add_argument( parser.add_argument(
"--dump_circular_buffer_size", "--dump_circular_buffer_size",
type=int, type=int,
default=1000, default=-1,
help="Size of the circular buffer used to dump execution events. " help="Size of the circular buffer used to dump execution events. "
"A value <= 0 disables the circular-buffer behavior and causes "
"all instrumented tensor values to be dumped. "
"This is relevant only when --dump_dir is set.") "This is relevant only when --dump_dir is set.")
parser.add_argument( parser.add_argument(
"--use_random_config_path", "--use_random_config_path",
@ -178,9 +180,9 @@ def main(_):
return activations return activations
# init model # init model
hidden = get_dense_weights(IMAGE_SIZE**2, HIDDEN_SIZE) hidden_weights = get_dense_weights(IMAGE_SIZE**2, HIDDEN_SIZE)
logits = get_dense_weights(HIDDEN_SIZE, NUM_LABELS) output_weights = get_dense_weights(HIDDEN_SIZE, NUM_LABELS)
variables = hidden + logits variables = hidden_weights + output_weights
@tf.function @tf.function
def model(x): def model(x):
@ -193,15 +195,25 @@ def main(_):
Returns: Returns:
A (?, 10) tensor containing the class scores for each example. A (?, 10) tensor containing the class scores for each example.
""" """
hidden_act = dense_layer(hidden, x) hidden_act = dense_layer(hidden_weights, x)
logits_act = dense_layer(logits, hidden_act, tf.identity) logits_act = dense_layer(output_weights, hidden_act, tf.identity)
y = tf.nn.softmax(logits_act) y = tf.nn.softmax(logits_act)
return y return y
@tf.function @tf.function
def loss(logits, labels): def loss(probs, labels):
"""Calculates cross entropy loss.""" """Calculates cross entropy loss.
diff = -(labels * tf.math.log(logits))
Args:
probs: Class probabilities predicted by the model. The shape is expected
to be (?, 10).
labels: Truth labels for the classes, as one-hot encoded vectors. The
shape is expected to be the same as `probs`.
Returns:
A scalar loss tensor.
"""
diff = -labels * tf.math.log(probs)
loss = tf.reduce_mean(diff) loss = tf.reduce_mean(diff)
return loss return loss