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https://github.com/tinygrad/tinygrad.git
synced 2026-04-29 03:00:14 -04:00
support drawing graphs
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@@ -15,18 +15,18 @@ class TinyConvNet:
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conv = 3
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inter_chan, out_chan = 8, 16 # for speed
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self.c1 = Tensor.uniform(inter_chan,3,conv,conv)
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self.bn1 = BatchNorm2D(inter_chan)
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#self.bn1 = BatchNorm2D(inter_chan)
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self.c2 = Tensor.uniform(out_chan,inter_chan,conv,conv)
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self.bn2 = BatchNorm2D(out_chan)
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#self.bn2 = BatchNorm2D(out_chan)
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self.l1 = Tensor.uniform(out_chan*6*6, classes)
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def forward(self, x):
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x = x.conv2d(self.c1).relu().max_pool2d()
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x = self.bn1(x)
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#x = self.bn1(x)
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x = x.conv2d(self.c2).relu().max_pool2d()
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x = self.bn2(x)
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#x = self.bn2(x)
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x = x.reshape(shape=[x.shape[0], -1])
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return x.dot(self.l1).logsoftmax()
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return x.dot(self.l1)
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if __name__ == "__main__":
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IMAGENET = os.getenv("IMAGENET") is not None
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@@ -9,21 +9,32 @@ import numpy as np
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DEBUG = os.getenv("DEBUG", None) is not None
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if DEBUG:
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G = None
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if os.getenv("GRAPH", None) is not None:
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import networkx as nx
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G = nx.DiGraph()
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import atexit, time
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debug_counts, debug_times = defaultdict(int), defaultdict(float)
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def print_debug_exit():
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for name, _ in sorted(debug_times.items(), key=lambda x: -x[1]):
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print(f"{name:>20} : {debug_counts[name]:>6} {debug_times[name]:>10.2f} ms")
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if G is not None:
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nx.drawing.nx_pydot.write_dot(G, '/tmp/net.dot')
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atexit.register(print_debug_exit)
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class ProfileOp:
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def __init__(self, name, x, backward=False):
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self.name, self.x, self.output = f"back_{name}" if backward else name, x, None
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self.name, self.x, self.output, self.backward = f"back_{name}" if backward else name, x, None, backward
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def __enter__(self):
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if DEBUG: self.st = time.time()
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return self
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def __exit__(self, *junk):
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if DEBUG:
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if G is not None:
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for x in self.x:
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for y in self.output:
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G.add_edge(id(x.data), id(y.data), label=self.name, color="blue" if self.backward else "black")
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G.nodes[id(x.data)]['label'], G.nodes[id(y.data)]['label'] = str(x.shape), str(y.shape)
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self.output[0].data.toCPU()
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et = (time.time()-self.st)*1000.
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debug_counts[self.name] += 1
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