From bff95a7f2a9c34dfc31c079e3936640f9b98ceb0 Mon Sep 17 00:00:00 2001
From: Prashant Khurana <github@prashantkhurana.com>
Date: Thu, 30 Mar 2023 04:51:41 +0530
Subject: [PATCH] Fix lab1 assertion dense layer output assertion 1)
tf.random.set_seed only sets the global seed
https://www.tensorflow.org/api_docs/python/tf/random/set_seed 2) we need to
set keras set_random_seed to make all seeds be deterministic. docs :
https://www.tensorflow.org/api_docs/python/tf/config/experimental/enable_op_determinism,
https://www.tensorflow.org/api_docs/python/tf/keras/utils/set_random_seed.
enable_op_determinism might not be needed here but its good to have.
fixes #116
---
lab1/Part1_TensorFlow.ipynb | 7 +++++--
mitdeeplearning/lab1.py | 4 ++--
2 files changed, 7 insertions(+), 4 deletions(-)
diff --git a/lab1/Part1_TensorFlow.ipynb b/lab1/Part1_TensorFlow.ipynb
index e9e43b1f..55d80c67 100644
--- a/lab1/Part1_TensorFlow.ipynb
+++ b/lab1/Part1_TensorFlow.ipynb
@@ -366,8 +366,11 @@
" y = # TODO\n",
" return y\n",
"\n",
- "# Since layer parameters are initialized randomly, we will set a random seed for reproducibility\n",
- "tf.random.set_seed(1)\n",
+ "# Since layer parameters are initialized randomly, we will set random seed for reproducibility \n",
+ "# and make operations deterministic\n",
+ "tf.keras.utils.set_random_seed(1)\n",
+ "tf.config.experimental.enable_op_determinism()\n",
+ "\n",
"layer = OurDenseLayer(3)\n",
"layer.build((1,2))\n",
"x_input = tf.constant([[1,2.]], shape=(1,2))\n",
diff --git a/mitdeeplearning/lab1.py b/mitdeeplearning/lab1.py
index 19d448a3..9ff0b658 100644
--- a/mitdeeplearning/lab1.py
+++ b/mitdeeplearning/lab1.py
@@ -80,8 +80,8 @@ def test_batch_func_next_step(func, args):
return True
def test_custom_dense_layer_output(y):
- true_y = np.array([[0.2697859, 0.45750418, 0.66536945]],dtype='float32')
+ true_y = np.array([[0.27064407, 0.1826951, 0.50374055]],dtype='float32')
assert tf.shape(y).numpy().tolist() == list(true_y.shape), "[FAIL] output is of incorrect shape. expected {} but got {}".format(true_y.shape, y.numpy().shape)
- np.testing.assert_almost_equal(y.numpy(), true_y, decimal=7, err_msg="[FAIL] output is of incorrect value. expected {} but got {}".format(y.numpy(), true_y), verbose=True)
+ np.testing.assert_almost_equal(y.numpy(), true_y, decimal=7, err_msg="[FAIL] output is of incorrect value. expected {} but got {}".format(true_y,y.numpy()), verbose=True)
print("[PASS] test_custom_dense_layer_output")
return True