I installed fenics on windows subsystem for linux to do my homework.I am trying to test fenics. So I use ft01_possion.py on the tutorial.
from fenics import *
# Create mesh and define function space
mesh = UnitSquareMesh(8, 8)
V = FunctionSpace(mesh, 'P', 1)
# Define boundary conditions
u_D = Expression('1 + x[0]*x[0] + 2*x[1]*x[1]', degree = 2)
def boundary(x, on_boundary):
return on_boundary
bc = DirichletBC(V, u_D, boundary)
# Define variational problem
u = TrialFunction(V)
v = TestFunction(V)
f = Constant(-6.0)
a = dot(grad(u), grad(v))*dx
L = f*v*dx
# Compute solution
u = Function(V)
solve(a == L, u, bc)
# Plot solution and mesh
plot(u)
plot(mesh)
interactive()
It did not show the figure.
the error i am getting is:
Solving linear variational problem.
Traceback (most recent call last):
File "ft01_poisson.py", line 29, in <module>
interactive()
NameError: name 'interactive' is not defined
I have tried to reinstall the newest version of fenics without success.
While the print out of the error values work, the NameError prevents the plots from being shown.
Some Fenics examples are unfortunately out of date. Please see the following GitHub post.
Change 'interactive()' to
import matplotlib.pyplot as plt
plt.show()
this will show your results.
Errors are shown as follows:
error_L2 = 0.008235098073354827
error_max = 1.3322676295501878e-15
But there is :NameError: name 'interactive' is not defined, probably this error is not affecting the results
Related
I've created a simple NLP model in PyTorch, trained it and it works as expected in Python.
Then I've exported it to the TorchScript with jit.trace. And loading it back into Python works fine and model works as expected.
But when I try to execute it in rust with tch-rs (Rust bindings for the C++ api of PyTorch), the following error occurs and I have no idea how to debug it:
Error: Torch("The following operation failed in the TorchScript interpreter.
Traceback of TorchScript, serialized code (most recent call last):
File \"code/__torch__/___torch_mangle_469.py\", line 17, in forward
dropout = self.dropout
bert = self.bert
_0 = (dropout).forward((bert).forward(input_id, mask, ), )
~~~~~~~~~~~~~ <--- HERE
_1 = (relu).forward((linear).forward(_0, ), )
return _1
File \"code/__torch__/transformers/models/bert/modeling_bert/___torch_mangle_465.py\", line 19, in forward
batch_size = ops.prim.NumToTensor(torch.size(input_id, 0))
_0 = int(batch_size)
seq_length = ops.prim.NumToTensor(torch.size(input_id, 1))
~~~~~~~~~~ <--- HERE
_1 = int(seq_length)
_2 = int(seq_length)
Traceback of TorchScript, original code (most recent call last):
/user/.conda/envs/tch/lib/python3.10/site-packages/transformers/models/bert/modeling_bert.py(954): forward
/user/.conda/envs/tch/lib/python3.10/site-packages/torch/nn/modules/module.py(1176): _slow_forward
/user/.conda/envs/tch/lib/python3.10/site-packages/torch/nn/modules/module.py(1192): _call_impl
/var/folders/zs/vmmy3w4n0ns1c0kj91skmfnm0000gn/T/ipykernel_10987/868892765.py(17): forward
/user/.conda/envs/tch/lib/python3.10/site-packages/torch/nn/modules/module.py(1176): _slow_forward
/user/.conda/envs/tch/lib/python3.10/site-packages/torch/nn/modules/module.py(1192): _call_impl
/user/.conda/envs/tch/lib/python3.10/site-packages/torch/jit/_trace.py(957): trace_module
/user/.conda/envs/tch/lib/python3.10/site-packages/torch/jit/_trace.py(753): trace
/var/folders/zs/vmmy3w4n0ns1c0kj91skmfnm0000gn/T/ipykernel_10987/749605851.py(1): <module>
/user/.conda/envs/tch/lib/python3.10/site-packages/IPython/core/interactiveshell.py(3430): run_code
/user/.conda/envs/tch/lib/python3.10/site-packages/IPython/core/interactiveshell.py(3341): run_ast_nodes
/user/.conda/envs/tch/lib/python3.10/site-packages/IPython/core/interactiveshell.py(3168): run_cell_async
/user/.conda/envs/tch/lib/python3.10/site-packages/IPython/core/async_helpers.py(129): _pseudo_sync_runner
/user/.conda/envs/tch/lib/python3.10/site-packages/IPython/core/interactiveshell.py(2970): _run_cell
/user/.conda/envs/tch/lib/python3.10/site-packages/IPython/core/interactiveshell.py(2941): run_cell
/user/.conda/envs/tch/lib/python3.10/site-packages/ipykernel/zmqshell.py(531): run_cell
/user/.conda/envs/tch/lib/python3.10/site-packages/ipykernel/ipkernel.py(380): do_execute
/user/.conda/envs/tch/lib/python3.10/site-packages/ipykernel/kernelbase.py(700): execute_request
/user/.conda/envs/tch/lib/python3.10/site-packages/ipykernel/kernelbase.py(383): dispatch_shell
/user/.conda/envs/tch/lib/python3.10/site-packages/ipykernel/kernelbase.py(496): process_one
/user/.conda/envs/tch/lib/python3.10/site-packages/ipykernel/kernelbase.py(510): dispatch_queue
/user/.conda/envs/tch/lib/python3.10/asyncio/events.py(80): _run
/user/.conda/envs/tch/lib/python3.10/asyncio/base_events.py(1868): _run_once
/user/.conda/envs/tch/lib/python3.10/asyncio/base_events.py(597): run_forever
/user/.conda/envs/tch/lib/python3.10/site-packages/tornado/platform/asyncio.py(212): start
/user/.conda/envs/tch/lib/python3.10/site-packages/ipykernel/kernelapp.py(701): start
/user/.conda/envs/tch/lib/python3.10/site-packages/traitlets/config/application.py(990): launch_instance
/user/.conda/envs/tch/lib/python3.10/site-packages/ipykernel_launcher.py(12): <module>
/user/.conda/envs/tch/lib/python3.10/runpy.py(75): _run_code
/user/.conda/envs/tch/lib/python3.10/runpy.py(191): _run_module_as_main
RuntimeError: Dimension out of range (expected to be in range of [-1, 0], but got 1)
")
And here is the simple model that I try to execute:
from torch import nn
from transformers import BertModel
class BertClassifier(nn.Module):
def __init__(self, dropout=0.5):
super(BertClassifier, self).__init__()
self.bert = BertModel.from_pretrained('bert-base-cased')
self.dropout = nn.Dropout(dropout)
self.linear = nn.Linear(768, 5)
self.relu = nn.ReLU()
def forward(self, input_id, mask):
_, pooled_output = self.bert(input_ids= input_id, attention_mask=mask,return_dict=False)
dropout_output = self.dropout(pooled_output)
linear_output = self.linear(dropout_output)
final_layer = self.relu(linear_output)
return final_layer
I'm new to ML and I can't find any docs on how to debug TorchScript runtime errors so I appreciate any help in solving this problem
I have successfully created a pytorch NN with 10 inputs and two output classes (B & S). So B is either 0 or 1, and S is either 0 or 1. So Y_test is B(0),B(1),S(0),S(1). Y_Pred will output B(0...1) and S(0...1). The net trains without error...
Now I want to create a confusion matrix and I am confused.
This is my code:
cm = confusion_matrix(y_test, y_pred)
print (cm)
It generates this error message:
"Traceback (most recent call last):
File "C:/Users/user/PycharmProjects/3_indexes_NN/3_indexes_NN.py", line 386, in "
[line 386 is cm = confusion_matrix(y_test, y_pred)]
cm = confusion_matrix(y_test, y_pred)
File "C:\Users\user\anaconda3\envs\PIMA\lib\site-packages\sklearn\metrics_classification.py", line 309, in confusion_matrix
raise ValueError("%s is not supported" % y_type)
ValueError: multilabel-indicator is not supported
I am completely lost. Can anyone help me understand where I've gone wrong?
Thank you in advance for throwing me a life-line!!
Can both S and B be 1 simultaneously? In this case, this is indeed a multilabel task, making confusion matrix an unsuitable metric.
Otherwise, you may work it around using something like y_pred.argmax(axis=1) for both.
I am using IBM's quantum computing lab, and was following a tutorial made by IBM for getting started, and my code is throwing errors. I followed the tutorial exactly. Here is my code:
#-----------Cell 1:
import numpy as np
# Importing standard Qiskit libraries
from qiskit import QuantumCircuit, transpile, Aer, IBMQ
from qiskit.tools.jupyter import *
from qiskit.visualization import *
from ibm_quantum_widgets import *
from qiskit.providers.aer import QasmSimulator
# Loading your IBM Quantum account(s)
provider = IBMQ.load_account()
#-----------Cell 2:
# Build
#------
# Create a Quantum Circuit acting on the q register
circuit = QuantumCircuit(2, 2)
# Add a H gate on qubit 0
circuit.h(0)
# Add a CX (CNOT) gate on control qubit 0 and target qubit 1
circuit.cx(0, 1)
# Map the quantum measurement to the classical bits
circuit.measure([0,1], [0,1])
# END
# Execute
#--------
# Use Aer's qasm_simulator
simulator = Aer.get_backend('qasm_simulator')
# Execute the circuit on the qasm simulator
job = execute(circuit, simulator, shots=1000)
# Grab results from the job
result = job.result()
# Return counts
counts = result.get_counts(circuit)
print("\nTotal count for 00 and 11 are:",counts)
# END
# Visualize
#----------
# Import draw_circuit, then use it to draw the circuit
from ibm_quantum_widgets import draw_circuit
draw_circuit(circuit)
# Analyze
#--------
# Plot a histogram
plot_histogram(counts)
# END
This code throws this error:
Traceback (most recent call last):
File "/tmp/ipykernel_59/1801586149.py", line 26, in <module>
job = execute(circuit, simulator, shots=1000)
NameError: name 'execute' is not defined
Use %tb to get the full traceback.
I am new to IBM and quantum computing, how do I fix this error?
Here is the tutorial I was following if you need it: https://quantum-computing.ibm.com/lab/docs/iql/first-circuit
You did not import execute from qiskit.
Change
from qiskit import QuantumCircuit, transpile, Aer, IBMQ
to
from qiskit import QuantumCircuit, transpile, Aer, IBMQ, execute
I'm trying to compare certain pixel values in my pyautogui script, but it crashes with following error message after either multiple successful runs, or sometimes just straight on the first call:
Traceback (most recent call last):
File "F:\Koodit\Python\HeroWars NNet\Assets\autodataGet.py", line 219, in <module>
battle = observeBattle()
File "F:\Koodit\Python\HeroWars NNet\Assets\autodataGet.py", line 180, in observeBattle
statii = getHeroBattlePixels()
File "F:\Koodit\Python\HeroWars NNet\Assets\autodataGet.py", line 32, in getHeroBattlePixels
colormatch = pyautogui.pixelMatchesColor(location[0], location[1], alive, tolerance=5)
File "E:\Program Files\Python\lib\site-packages\pyscreeze\__init__.py", line 557, in pixelMatchesColor
pix = pixel(x, y)
File "E:\Program Files\Python\lib\site-packages\pyscreeze\__init__.py", line 582, in pixel
return (r, g, b)
File "E:\Program Files\Python\lib\contextlib.py", line 120, in __exit__
next(self.gen)
File "E:\Program Files\Python\lib\site-packages\pyscreeze\__init__.py", line 111, in __win32_openDC
raise WindowsError("windll.user32.ReleaseDC failed : return 0")
OSError: windll.user32.ReleaseDC failed : return 0
My code (this is called multiple times, sometimes it crashes on first run, sometimes it runs nicely for around 100 calls before failing, also, my screen is 4K, so the resolutions get big):
def getSomePixelStatuses():
someLocations= [
[1200, 990],
[1300, 990],
[1400, 990],
[1500, 990],
[1602, 990],
[1768, 990],
[1868, 990],
[1968, 990],
[2068, 990],
[2169, 990]
]
status = []
someValue= (92, 13, 12)
for location in someLocations:
colormatch = pyautogui.pixelMatchesColor(location[0], location[1], someValue, tolerance=5)
status.append(colormatch)
return status
I have no idea how to mitigate this problem. It would seem that pyautogui uses pyscreeze to read pixel values on screen, and most probable candidate for the place where error occurs is the pyscreeze pixel function:
def pixel(x, y):
"""
TODO
"""
if sys.platform == 'win32':
# On Windows, calling GetDC() and GetPixel() is twice as fast as using our screenshot() function.
with __win32_openDC(0) as hdc: # handle will be released automatically
color = windll.gdi32.GetPixel(hdc, x, y)
if color < 0:
raise WindowsError("windll.gdi32.GetPixel failed : return {}".format(color))
# color is in the format 0xbbggrr https://msdn.microsoft.com/en-us/library/windows/desktop/dd183449(v=vs.85).aspx
bbggrr = "{:0>6x}".format(color) # bbggrr => 'bbggrr' (hex)
b, g, r = (int(bbggrr[i:i+2], 16) for i in range(0, 6, 2))
return (r, g, b)
else:
# Need to select only the first three values of the color in
# case the returned pixel has an alpha channel
return RGB(*(screenshot().getpixel((x, y))[:3]))
I installed these libraries just yesterday, and I'm running python 3.8 on windows 10, and pyscreeze is version 0.1.25 so in theory everything should be up to date, but somehow something ends up crashing. Is there a way to mitigate this, either modifying my code, or even the library itself, or is my environment not suitable for this operation?
Well I know it's not particularly helpful; but for me, this error was fixed simply by running my code on 3.7 instead of 3.8. There shouldn't be any changes you have to make to your code, however (unless you were using walrus!)
On Windows, this can be done with the -3.7 command line flag, as long as 3.7 is installed
PyScreeze and PyAutoGUI maintainer here. This is an issue that has been fixed in PyScreeze 0.1.28, so you just need to update it by running pip install -U pyscreeze.
For more context, here's the GitHub issue where it was reported: https://github.com/asweigart/pyscreeze/pull/73
It's a bug. You were on the right track, as the problem is indeed in this line of the pixel() function:
with __win32_openDC(0) as hdc
That function uses cyptes.windll which doesn't seem to do well with the negative values sometimes returned from windll.user32.GetDC(), which subsequently creates an exception when windll.user32.ReleaseDC() is called.
The folks at pillow helped track this down and propose a fix.
issue filed at pyautogui
issue filed at pillow which led to the solution
pending PR at pyscreeze to address
I can use pixel function on Python 3.8 like this:
try:
a = pixel(100,100)
> except:
> a = pixel(100,100)
I don't have any clue why this works, but it works.
I had this error too and i fixed it. Just use try and except.
While true:
try:
x,y = pyautogui.position()
print(pyautogui.pixel(x,y))
except:
print("Cannot get pixel for the moment")
Given that you might be taking pixels multiple times, or you can do so, try and except works wonders to solve any pyscreeze for pyautogui issue. Honestly i dont know whats up with pyscreeze, but this works for me. Cheers
When I try to solve this first ode by using Sympy as it shows below:
import sympy
y = sympy.Function('y')
t = sympy.Symbol('t')
ode = sympy.Eq(y(t).diff(t),(1/y(t))*sympy.sin(t))
sol = sympy.dsolve(ode,y(t))
csol=sol.subs([(t,0),(y(0),-4)]) # the I.C. is y(0) = 1
ode_sol= sol.subs([(csol.rhs,csol.lhs)])
print(sympy.pprint(ode_sol))
It gives me this error:
Traceback (most recent call last):
File "C:/Users/Mohammed Alotaibi/AppData/Local/Programs/Python/Python35/ODE2.py", line 26, in <module>
csol=sol.subs([(t,0),(y(0),-4)]) # the I.C. is y(0) = 1
AttributeError: 'list' object has no attribute 'subs'
Your problem is that this ODE does not have a unique solution. Thus it returns a list of solution, which you can find out from the error message and by printing sol.
Do the evaluation in a loop,
for psol in sol:
csol = psol.subs([(t,0),(y(0),-4)]);
ode_sol = psol.subs([(csol.rhs,csol.lhs)]);
print(sympy.pprint(ode_sol))
to find the next error, that substituting does not solve for the constant. What works is to define C1=sympy.Symbol("C1") and using
ode_sol= psol.subs([(C1, sympy.solve(csol)[0])]);
but this still feels hacky. Or better to avoid error messages for the unsolvability of the second case:
C1=sympy.Symbol("C1");
for psol in sol:
csol = psol.subs([(t,0),(y(0),-4)]);
for cc1 in sympy.solve(csol):
ode_sol= psol.subs([(C1, cc1)]);
print(sympy.pprint(ode_sol))