julianser / hed-dlg-latent-piecewise-norm Goto Github PK
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License: GNU General Public License v3.0
We have found a possible potential migration to f-strings.
We have found a possible potential migration to f-strings.
We have found a possible potential migration to f-strings.
We have found a possible potential migration to f-strings.
Consider using a more descriptive function name for DPrint, such as DebugPrint.
Replace cPickle with the pickle module for compatibility with Python 3.
Replace cPickle with the pickle module for Python 3 compatibility.
Replace 'cPickle' with 'pickle' for Python 3 compatibility.
Replace string representations of lambda functions with actual lambda functions.
Consider using more descriptive variable names for 'train_iterator_offset' and 'train_iterator_reshuffle_count'.
Remove unused imports to improve code readability.
Avoid using dict.update() for updating instance attributes. Assign attributes explicitly for better readability and maintainability.
Fix the attribute name to 'exit_flag' to match the correct attribute in the SSFetcher class.
Consider making the maxsize of the queue configurable instead of hardcoding it.
Consider using 'import numpy as np' and 'import warnings as wrn' to follow common conventions and improve readability.
Consider using a more explicit version check instead of checking for the existence of 'argpartition' attribute.
Consider using a multiline string with triple double quotes (""") instead of triple single quotes (''') for better readability and consistency.
This fallback implementation of 'argpartition' using 'numpy.argsort' may not have the same performance characteristics as the intended 'numpy.argpartition'. Consider adding a comment to explain the potential performance impact.
Consider using a more modern deep learning library like TensorFlow or PyTorch instead of Theano, which is no longer actively developed.
Add a docstring to the 'sharedX' function to explain its purpose, parameters, and return value.
Add a docstring to the 'Adam' function to explain its purpose, parameters, and return value.
Use a more descriptive variable name instead of 'i' to improve code readability.
Use more descriptive variable names instead of 'p' and 'g' to improve code readability.
Consider using more modern libraries like PyTorch or TensorFlow instead of Theano, which is no longer actively developed.
Add a basic logging configuration to control the log level and format.
Instead of storing the floatX value as an instance variable, consider using it directly from the theano.config when needed.
Use a dictionary comprehension instead of a list comprehension inside dict() for better readability.
Use 'if unknown:' instead of checking the length of the set to make the code more Pythonic.
Replace cPickle with the pickle module for Python 3 compatibility.
Use the print function with formatted strings for Python 3 compatibility.
The Timer class is not used in the code and should be removed.
The logger is not used in the code and should be removed or logging statements should be added.
Replace assert statements with proper error handling and informative error messages.
Raise a ValueError with an informative error message instead of using print statements for error handling.
Consider removing unused imports 'sys' and 'getopt'.
Group standard library imports together and separate them from third-party imports.
Replace 'xrange' with 'range' for Python 3 compatibility.
Use 'numpy' instead of 'np' for consistency with the rest of the code.
Consider renaming the class 'Iterator' to a more descriptive name, such as 'DialogueIterator', to avoid confusion with built-in or generic iterators.
Replace cPickle with the more modern 'pickle' module.
Use 'if line_words[-1] != '': line_words.append('')' for better readability.
This line is redundant, as it creates a new list 's' that is identical to 'line_words'. Remove this line and use 'line_words' directly.
Use 'unknowns += word_id == 0' for better readability.
Use 'logger.info("Mean document length %f", float(sum(map(len, binarized_corpus))/len(binarized_corpus)))' for better readability.
Replace cPickle with the pickle module for Python 3 compatibility.
Remove the codecs import as it is not used in the code.
In Python 3, you can simply use 'class Sampler:' instead of 'class Sampler(object):'.
Consider using a list comprehension instead of map and lambda for better readability.
Replace the map function with a list comprehension for better readability.
Consider using a ternary expression to simplify the code.
Consider using a ternary expression to simplify the code.
Replace cPickle with the more modern 'pickle' module.
Avoid using wildcard imports, as they can lead to unexpected behavior and make the code harder to understand.
Avoid using wildcard imports, as they can lead to unexpected behavior and make the code harder to understand.
Consider using a more descriptive function name, such as 'append_and_return_param', to improve code readability.
Replace cPickle with the more modern 'pickle' library.
Using 'self.dict.update()' can lead to unexpected behavior and make the code harder to understand. Consider using a more explicit way to update the object's attributes.
Avoid using 'eval()' as it can lead to security vulnerabilities and make the code harder to understand. Consider using a safer alternative, such as a dictionary mapping strings to functions.
Remove the duplicate shebang line.
Replace cPickle with the more modern 'pickle' module.
Remove the unused 'sys' import.
Replace 'math' module with 'numpy' functions for consistency.
Consider using the 'timeit' module instead of a custom Timer class.
Use a more descriptive variable name instead of 'bs'.
Raise an exception with a more specific error message if the model path is not valid.
Use 'if lines:' instead of 'if len(lines):' for checking if the list is not empty.
Use a 'with' statement to ensure the file is properly closed after writing.
Replace cPickle with the more modern 'pickle' module.
Remove unused import 'argpartition' from 'numpy_compat'.
The Timer class is not used in the code, consider removing it.
Use a more Pythonic way to check if the file exists, like 'try' and 'except' with FileNotFoundError.
Use 'with' statement to handle file opening and closing automatically.
Replace the deprecated 'print >>' syntax with 'print()' function and 'file' parameter.
Replace cPickle with the more modern 'pickle' module.
Use 'import numpy as np' to follow the common convention.
Remove or replace the 'if False==True:' statement, as it is unnecessary and confusing.
Replace print statements with proper logging.
Specify the file mode when opening a file, e.g., 'with open(state_path, 'rb') as src:'.
Refactor the model loading process into a separate function for better code organization.
Replace magic numbers like '3' with named constants for better code readability.
Replace cPickle with the pickle module for Python 3 compatibility.
Consider loading the state from a file or using a function to initialize the state with default values.
Use a function to load the model and handle exceptions within the function.
Use 'if lines:' instead of 'if len(lines):' to check if the list is not empty.
Replace print statements with logging calls for better control over output.
Replace assert statements with proper error handling, such as raising a custom exception with a descriptive error message.
Consider using a progress bar library like tqdm to display progress instead of manually printing progress updates.
Replace magic numbers like 3 with named constants for better code readability.
Use 'with' statement when opening a file to ensure proper closing, e.g., 'with open(args.test_dialogues, 'r') as f: test_dialogues = f.readlines()'.
Use 'string.ascii_lowercase' instead of manually defining the alphabet.
Use 'os.path.splitext' to extract the file extension instead of slicing the string.
Use 'np.zeros' instead of 'numpy.zeros' for consistency with common conventions.
Replace 'iterkeys()' with 'keys()' for compatibility with Python 3.
Place each import statement on a separate line for better readability.
Consider using 'StandardScaler' from 'sklearn.preprocessing' for better control over scaling.
Replace 'NormalInit' with 'numpy.random.normal' for generating random numbers from a normal distribution.
The tf function is not used in the code and should be removed.
Variables f1 and f2 are not defined. Remove these lines or define the variables.
Use a context manager (with statement) to open and close the file properly.
Use a context manager (with statement) to open and close the file properly.
unique_words should be a set instead of a dictionary for better performance and readability.
If unique_words is a set, use the add method instead: unique_words.add(word)
Use the format method or f-strings for better readability.
Use the format method or f-strings for better readability.
If unique_words is a set, use len(unique_words) instead.
Replace cPickle with the pickle module for Python 3 compatibility.
The Timer class is not used in the code and should be removed.
Consider using a more descriptive variable name instead of 'bs'.
Use 'if lines:' instead of 'if len(lines):' to check if the list is not empty.
Use the print function with string formatting for better readability and Python 3 compatibility.
Remove this print statement as it seems to be a debugging leftover.
Move the commented example usage to the argparse help or a separate documentation section.
Remove unused import 'randint'.
Use 'with' statement to open files to ensure they are closed properly.
Use 'if not x_count or not y_count:' instead of comparing with 1.
Use a constant variable for the threshold value instead of hardcoding it.
Move the main code block into a separate function and call it inside the 'if name == "main":' block.
Consider importing only the necessary functions and classes instead of using wildcard imports.
Add a docstring to the getattr method to explain its purpose and usage.
Explain the purpose of changing sys.stdout to an instance of the Unbuffered class with a comment.
Consider using single quotes for string literals to maintain consistency in the code.
Simplify the condition by removing the '== True' part.
Consider using a context manager (with statement) when opening files to ensure they are properly closed.
Use a context manager (with statement) to handle file opening and closing.
Consider using a more descriptive variable name for PRINT_VARS, such as PRINT_VARIABLES.
Consider using numpy.isfinite(c) instead of checking for both inf and nan separately.
Replace cPickle with the pickle module for Python 3 compatibility.
Remove unused import 'traceback'.
Remove unused import 'sys'.
Remove unused import 'os'.
Remove unused import 'numpy'.
Remove unused import 'codecs'.
Remove unused import 'search'.
Remove unused import 'utils'.
Remove unused import 'DialogEncoderDecoder'.
Remove unused import 'argpartition'.
Remove unused import 'prototype_state'.
Remove unused 'logger' variable.
Remove unused 'Timer' class.
Replace 'if len(lines):' with 'if lines:' to check if the list is not empty.
Use a context manager (with statement) to handle file opening and closing.
Replace cPickle with the pickle module for Python 3 compatibility.
This function is not used in the code and should be removed.
These lines reference undefined variables f1 and f2. Remove or replace them with the correct variables.
These variables should be integers, not floats.
Use a set instead of a dictionary for unique_words.
Replace this line with 'unique_words.add(word)' if using a set for unique_words.
Use parentheses for print statements to ensure Python 3 compatibility.
Use parentheses for print statements to ensure Python 3 compatibility.
Use parentheses for print statements to ensure Python 3 compatibility.
Consider adding a docstring to the sharedX function to explain its purpose and usage.
Consider adding a docstring to the Adam function to explain its purpose and usage.
Consider adding a docstring to the Adagrad function to explain its purpose and usage.
Consider adding a docstring to the Adadelta function to explain its purpose and usage.
Consider adding a docstring to the RMSProp function to explain its purpose and usage.
Consider adding a docstring to the Maxout class to explain its purpose and usage.
Consider adding a docstring to the UniformInit function to explain its purpose and usage.
Consider adding a docstring to the OrthogonalInit function to explain its purpose and usage.
Consider adding a docstring to the GrabProbs function to explain its purpose and usage.
Consider adding a docstring to the NormalInit function to explain its purpose and usage.
Consider adding a docstring to the NormalInit3D function to explain its purpose and usage.
Consider adding a docstring to the ConvertTimedelta function to explain its purpose and usage.
Consider adding a docstring to the SoftMax function to explain its purpose and usage.
Consider adding a docstring to the stable_log function to explain its purpose and usage.
Consider adding a docstring to the NormalizationOperator function to explain its purpose and usage.
Consider adding a docstring to the FeedforwardBatchNormalization function to explain its purpose and usage.
Consider adding a docstring to the RecurrentBatchNormalization function to explain its purpose and usage.
Consider adding a docstring to the LayerNormalization function to explain its purpose and usage.
Consider adding a docstring to the BatchedDot function to explain its purpose and usage.
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