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.tippy-popper { | |
max-width: 10000px !important; | |
} |
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.monaco-decorations-style-2::after, | |
.monaco-decorations-style-12::after { | |
display: none; | |
} |
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.monaco-icon-label-description-container::after { | |
display: none; | |
} |
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with tf.name_scope('summaries'): | |
tf.summary.scalar('min', tf.reduce_min(var)) # or | |
tf.reduce_min(var, name='min') |
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import torch | |
from torch.autograd import Variable | |
N, D_in, H, D_out = 64, 1000, 100, 10 | |
x = Variable(torch.randn(N, D_in), requires_grad=False) | |
y = Variable(torch.randn(N, D_out), requires_grad=False) | |
w1 = Variable(torch.randn(D_in, H), requires_grad=True) | |
w2 = Variable(torch.randn(H, D_out), requires_grad=True) | |
learning_rate = 1e-6 |
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import tensorflow as tf | |
import numpy as np | |
tfe = tf.contrib.eager | |
tf.enable_eager_execution() | |
N, D_in, H, D_out = 64, 1000, 100, 10 | |
x = tf.constant(np.random.rand(N, D_in)) | |
y = tf.constant(np.random.rand(N, D_out)) |
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import caffe | |
import numpy as np | |
transformer = caffe.io.Transformer({'data':net.blobs['data'].data.shape}) | |
transformer.set_transpose('data', (2,0,1)) | |
transformer.set_mean('data', mu) | |
transformer.set_raw_scale('data', 255) | |
transformer.set_channel_swap('data', (2,1,0)) | |
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test.pt | |
name: "AlexNet" | |
input: "data" | |
input_dim: 1 input_dim: 3 input_dim: 64 input_dim: 64 | |
layer { | |
name: "conv1" type: "Convolution" bottom: "data" top: "conv1" | |
param { lr_mult: 1 decay_mult: 1 } | |
param { lr_mult: 2 decay_mult: 0 } |
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{ 8'd255, 8'd0, 8'd255, 8'd255, 8'd127, 8'd127, 8'd255 } | |
{ 8'd0, 8'd255, 8'd127, 8'd0, 8'd255, 8'd255, 8'd255 } | |
{ 8'd0, 8'd0, 8'd0, 8'd255, 8'd127, 8'd127, 8'd0 } |
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// Type I | |
{ 4'd0, 4'd0 }, { 4'd0, 4'd1 }, { 4'd0, 4'd2 }, { 4'd0, 4'd3 }, | |
{ 4'd0, 4'd0 }, { 4'd1, 4'd0 }, { -4'd1, 4'd0 }, { -4'd2, 4'd0 }, | |
{ 4'd0, 4'd0 }, { 4'd0, 4'd1 }, { 4'd0, 4'd2 }, { 4'd0, 4'd3 }, | |
{ 4'd0, 4'd0 }, { 4'd1, 4'd0 }, { -4'd1, 4'd0 }, { -4'd2, 4'd0 }, | |
// Type J | |
{ 4'd0, 4'd0 }, { -4'd1, 4'd0 }, { 4'd0, 4'd1 }, { 4'd1, 4'd1 }, | |
{ 4'd0, 4'd0 }, { 4'd0, -4'd0 }, { 4'd0, 4'd1 }, { -4'd1, 4'd1 }, | |
{ -4'd1, 4'd0 }, { -4'd1, 4'd1 }, { 4'd0, 4'd1 }, { 4'd1, 4'd1 }, |
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