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d2l-ai · Mar 13, 2022 · 9908428 · 9908428
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commit 9908428
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Showing 7 changed files with 12 additions and 15 deletions.
diff --git a/Jenkinsfile b/Jenkinsfile
@@ -7,7 +7,7 @@ stage("Build and Publish") {
   def TARGET_BRANCH = env.CHANGE_TARGET ? env.CHANGE_TARGET : env.BRANCH_NAME
   // such as d2l-en-master
   def TASK = REPO_NAME + '-' + TARGET_BRANCH
-  node {
+  node('d2l-worker') {
     ws("workspace/${TASK}") {
       checkout scm
       // conda environment

diff --git a/chapter_appendix-mathematics-for-deep-learning/geometry-linear-algebraic-ops.md b/chapter_appendix-mathematics-for-deep-learning/geometry-linear-algebraic-ops.md
@@ -419,7 +419,7 @@ w = (ave_1 - ave_0).T
 predictions = X_test.reshape(2000, -1) @ (w.flatten()) > -1500000
 
 # Accuracy
-torch.mean(predictions.type(y_test.dtype) == y_test, dtype=torch.float64)
+torch.mean((predictions.type(y_test.dtype) == y_test).float(), dtype=torch.float64)
 ```
 
 ```{.python .input}

diff --git a/chapter_appendix-tools-for-deep-learning/d2l.md b/chapter_appendix-tools-for-deep-learning/d2l.md
@@ -10,7 +10,6 @@ As implementações dos seguintes membros do pacote `d2l` e seções onde eles s
 
 .. automodule:: d2l.mxnet
    :members:
-   :imported-members:
 
 ```
 
@@ -22,7 +21,6 @@ As implementações dos seguintes membros do pacote `d2l` e seções onde eles s
 
 .. automodule:: d2l.torch
    :members:
-   :imported-members:
 
 ```
 
@@ -35,7 +33,6 @@ As implementações dos seguintes membros do pacote `d2l` e seções onde eles s
 
 .. automodule:: d2l.tensorflow
    :members:
-   :imported-members:
 
 ```
 

diff --git a/chapter_computer-vision/kaggle-dog.md b/chapter_computer-vision/kaggle-dog.md
@@ -358,7 +358,7 @@ def train(net, train_iter, valid_iter, num_epochs, lr, wd, devices, lr_period,
                              (metric[0] / metric[1], None))
         if valid_iter is not None:
             valid_loss = evaluate_loss(valid_iter, net, devices)
-            animator.add(epoch + 1, (None, valid_loss))
+            animator.add(epoch + 1, (None, valid_loss.detach().cpu()))
         scheduler.step()
     if valid_iter is not None:
         print(f'train loss {metric[0] / metric[1]:.3f}, '

diff --git a/chapter_linear-networks/linear-regression.md b/chapter_linear-networks/linear-regression.md
@@ -343,7 +343,7 @@ em vez de escrever *loops for* custosos em Python.**)
 %matplotlib inline
 from d2l import mxnet as d2l
 import math
-from mxnet import np
+import numpy as np
 import time
 ```
 

diff --git a/setup.py b/setup.py
@@ -3,10 +3,10 @@
 
 requirements = [
     'jupyter==1.0.0',
-    'numpy==1.18.5',
-    'matplotlib==3.3.3',
+    'numpy==1.22.2',
+    'matplotlib==3.4',
     'requests==2.25.1',
-    'pandas==1.2.2'
+    'pandas==1.2.4'
 ]
 
 setup(

diff --git a/static/build.yml b/static/build.yml
@@ -4,10 +4,10 @@ dependencies:
   - pip:
     - ..  # d2l
     - git+https://github.com/d2l-ai/d2l-book
-    - mxnet-cu101==1.7.0
-    - torch==1.8.1+cu101
+    - mxnet-cu102==1.7.0
+    - torch==1.10.2+cu102
     - -f https://download.pytorch.org/whl/torch_stable.html
-    - torchvision==0.9.1+cu101
+    - torchvision==0.11.3+cu102
     - -f https://download.pytorch.org/whl/torch_stable.html
-    - tensorflow==2.3.1
-    - tensorflow-probability==0.11.1
+    - tensorflow==2.8.0
+    - tensorflow-probability==0.16.0