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added tensorboard support

pull/5/head
Thalles 2020-02-19 19:42:45 -03:00
parent f8ade33008
commit 3344165c75
3 changed files with 13 additions and 12 deletions
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20
FeatureEvaluation.ipynb
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@ -156,7 +156,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 8, "execution_count": 16,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
@ -177,7 +177,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 9, "execution_count": 17,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
@ -195,7 +195,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 11, "execution_count": 18,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
@ -298,7 +298,7 @@
"<All keys matched successfully>" "<All keys matched successfully>"
] ]
}, },
"execution_count": 11, "execution_count": 18,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
@ -323,7 +323,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 12, "execution_count": 19,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
@ -350,7 +350,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 13, "execution_count": 20,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
@ -377,7 +377,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 14, "execution_count": 21,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
@ -402,7 +402,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 15, "execution_count": 22,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
@ -410,8 +410,8 @@
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"SimCLR feature evaluation\n", "SimCLR feature evaluation\n",
"Train score: 0.4858\n", "Train score: 0.7444\n",
"Test score: 0.37825\n" "Test score: 0.62625\n"
] ]
} }
], ],

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model/checkpoint.pth
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5
train.py
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@ -62,7 +62,7 @@ for i in range(batch_size):
n_iter = 0 n_iter = 0
for e in range(config['epochs']): for e in range(config['epochs']):
for step, (batch_x, _) in enumerate(train_loader): for step, (batch_x, _) in enumerate(train_loader):
# print("Input batch:", batch_x.shape, torch.min(batch_x), torch.max(batch_x))
optimizer.zero_grad() optimizer.zero_grad()
xis = [] xis = []
@ -104,7 +104,8 @@ for e in range(config['epochs']):
negatives = torch.cat([zjs, zis], dim=0) negatives = torch.cat([zjs, zis], dim=0)
if use_cosine_similarity: if use_cosine_similarity:
l_neg = similarity_dim2(zis.view(batch_size, 1, out_dim), negatives.view(1, (2 * batch_size), out_dim)) negatives = negatives.view(1, (2 * batch_size), out_dim)
l_neg_1 = similarity_dim2(zis.view(batch_size, 1, out_dim), negatives)
else: else:
l_neg = torch.tensordot(zis.view(batch_size, 1, out_dim), negatives.T.view(1, out_dim, (2 * batch_size)), l_neg = torch.tensordot(zis.view(batch_size, 1, out_dim), negatives.T.view(1, out_dim, (2 * batch_size)),
dims=2) dims=2)