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import tensorflow as tf | |
import numpy as np | |
from IPython.display import clear_output, Image, display, HTML | |
def strip_consts(graph_def, max_const_size=32): | |
"""Strip large constant values from graph_def.""" | |
strip_def = tf.GraphDef() | |
for n0 in graph_def.node: | |
n = strip_def.node.add() | |
n.MergeFrom(n0) | |
if n.op == 'Const': | |
tensor = n.attr['value'].tensor | |
size = len(tensor.tensor_content) | |
if size > max_const_size: | |
tensor.tensor_content = tf.compat.as_bytes("<stripped %d bytes>"%size) | |
return strip_def | |
def rename_nodes(graph_def, rename_func): | |
res_def = tf.GraphDef() | |
for n0 in graph_def.node: | |
n = res_def.node.add() | |
n.MergeFrom(n0) | |
n.name = rename_func(n.name) | |
for i, s in enumerate(n.input): | |
n.input[i] = rename_func(s) if s[0]!='^' else '^'+rename_func(s[1:]) | |
return res_def | |
def show_graph(graph_def, max_const_size=32, width=800, height=600): | |
"""Visualize TensorFlow graph.""" | |
if hasattr(graph_def, 'as_graph_def'): | |
graph_def = graph_def.as_graph_def() | |
strip_def = strip_consts(graph_def, max_const_size=max_const_size) | |
code = """ | |
<script> | |
function load() {{ | |
document.getElementById("{id}").pbtxt = {data}; | |
}} | |
</script> | |
<link rel="import" href="https://tensorboard.appspot.com/tf-graph-basic.build.html" onload=load()> | |
<div style="height:{height}px"> | |
<tf-graph-basic id="{id}"></tf-graph-basic> | |
</div> | |
""".format(data=repr(str(strip_def)), id='graph'+str(np.random.rand()), height=str(height)) | |
iframe = """ | |
<iframe seamless style="width:{width}px;height:{height}px;border:0" srcdoc="{code}"></iframe> | |
""".format(code=code.replace('"', '"'), width=width, height=str(height + 20)) | |
display(HTML(iframe)) |
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