Compilation error

[sumantkrsoni]

Hello,
I want to code according to the pydens and during compilation I am using an error at "dg solver line".
Kindly fix it ASAP so that I can move further to code my problem.

I am using tensorflow 1.15 version
======================code================

%tensorflow_version 1.x
import os
import sys

Stop TF from showing unnecessary deprecation warnings

import warnings
warnings.filterwarnings('ignore')
from tensorflow import logging
logging.set_verbosity(logging.ERROR)
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'

import numpy as np
import tensorflow as tf
from tqdm import tqdm_notebook
import matplotlib.pyplot as plt

sys.path.append('..') # this line is not needed if PyDEns is installed as package
from pydens import Solver, NumpySampler, cart_prod, add_tokens
from pydens import plot_loss, plot_pair_1d, plot_2d, plot_sections_2d, plot_sections_3d

add_tokens()

describing pde-problem in pde-dict

pde = {
'n_dims': 1,
'form': lambda u, t: D(u, t) - 2 * np.pi * cos(2 * np.pi * t),
'initial_condition': 1
}

put it together in model-config

config = {
'pde': pde,
'track': {'dt': lambda u, t: D(u, t)} # allows to later fetch this value from the model
}

uniform sampling scheme

s = NumpySampler('uniform')

train the network on batches of 100 points

dg = Solver(config)
dg.fit(batch_size=100, sampler=s, n_iters=2000, bar='notebook')

plot_loss(dg.loss, color='cornflowerblue')

plot real solution and network approximation

pts = np.linspace(0, 1, 200).reshape(-1, 1)
sol = lambda t: np.sin(2 * np.pi * t) + 1
true = [sol(t[0]) for t in pts]
approxs = dg.solve(pts)

plt.plot(pts, true, 'b--', linewidth=3, label='True solution')
plt.plot(pts, approxs, 'r', label='Network approximation')
plt.xlabel(r'$t$', fontdict={'fontsize': 14})
plt.legend()
plt.show()

plot approximation of solution-derivative

der = lambda t: 2 * np.pi * np.cos(2 * np.pi * t)
true_der = [der(t[0]) for t in pts]
ders = dg.solve(pts, fetches='dt')

plt.plot(pts, true_der, 'b--', linewidth=3, label=r'True derivative')
plt.plot(pts, ders, 'r', label=r'Network approximation of $\frac{d u}{d t}$')
plt.xlabel(r'$t$', fontdict={'fontsize': 14})
plt.legend()
plt.show()

plot_pair_1d(model=dg,
solution=lambda t: np.sin(2np.pit)+1,
confidence=0.15, alpha=0.2)

plot_pair_1d(model=dg,
solution=lambda t: 2 * np.pi * np.cos(2 * np.pi * t),
fetches='dt')

---

======================error is====================
OperatorNotAllowedInGraphError Traceback (most recent call last)
in ()
40
41 # train the network on batches of 100 points
---> 42 dg = Solver(config)
43 dg.fit(batch_size=100, sampler=s, n_iters=2000, bar='notebook')
44

15 frames
/tensorflow-1.15.2/python3.6/tensorflow_core/python/framework/ops.py in _disallow_in_graph_mode(self, task)
521 raise errors.OperatorNotAllowedInGraphError(
522 "{} is not allowed in Graph execution. Use Eager execution or decorate"
--> 523 " this function with @tf.function.".format(task))
524
525 def _disallow_bool_casting(self):

OperatorNotAllowedInGraphError: iterating over tf.Tensor is not allowed in Graph execution. Use Eager execution or decorate this function with @tf.function.

[malmajid]

Did you find a solution for this? I'm using TensorFlow version 1.15.

[sumantkrsoni]

@malmajid
Not able to run this code.

Thanks