Adding LSTM algorithm from scratch in neural network algorithm sections #12082
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neural_network/lstm.py
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| ##### Testing ##### | ||
| # lstm.test() | ||
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| # testing can be done by uncommenting the above lines of code. |
There was a problem hiding this comment.
An error occurred while parsing the file: neural_network/lstm.py
Traceback (most recent call last):
File "/opt/render/project/src/algorithms_keeper/parser/python_parser.py", line 146, in parse
reports = lint_file(
^^^^^^^^^^
libcst._exceptions.ParserSyntaxError: Syntax Error @ 317:1.
parser error: error at 317:62: expected INDENT
# testing can be done by uncommenting the above lines of code.
^
for more information, see https://pre-commit.ci
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neural_network/lstm.py
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| self.char_to_idx = {c: i for i, c in enumerate(self.chars)} | ||
| self.idx_to_char = {i: c for i, c in enumerate(self.chars)} | ||
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| self.train_X, self.train_y = self.data[:-1], self.data[1:] |
There was a problem hiding this comment.
Variable and function names should follow the snake_case naming convention. Please update the following name accordingly: train_X
| self.initialize_weights() | ||
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| ##### Helper Functions ##### | ||
| def one_hot_encode(self, char: str) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function one_hot_encode
| vector[self.char_to_idx[char]] = 1 | ||
| return vector | ||
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| def initialize_weights(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function initialize_weights
| self.wy = self.init_weights(self.hidden_dim, self.char_size) | ||
| self.by = np.zeros((self.char_size, 1)) | ||
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| def init_weights(self, input_dim: int, output_dim: int) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function init_weights
neural_network/lstm.py
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| np.sqrt(6 / (input_dim + output_dim)) | ||
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| ##### Activation Functions ##### | ||
| def sigmoid(self, x: np.ndarray, derivative: bool = False) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function sigmoid
Please provide descriptive name for the parameter: x
neural_network/lstm.py
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| self.input_gates = {} | ||
| self.outputs = {} | ||
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| def forward(self, inputs: list) -> list: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function forward
neural_network/lstm.py
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| return outputs | ||
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| def backward(self, errors: list, inputs: list) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function backward
| [d_bf, d_bi, d_bc, d_bo, d_by]): | ||
| param -= self.lr * grad | ||
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| def train(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function train
neural_network/lstm.py
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| # Backward pass and weight updates | ||
| self.backward(errors, inputs) | ||
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| def predict(self, inputs: list) -> str: |
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As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function predict
neural_network/lstm.py
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| output = self.forward(inputs)[-1] | ||
| return self.idx_to_char[np.argmax(self.softmax(output))] | ||
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| def test(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function test
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neural_network/lstm.py
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| # lstm.train() | ||
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| # # Test the LSTM network and compute accuracy | ||
| # lstm.test() |
There was a problem hiding this comment.
An error occurred while parsing the file: neural_network/lstm.py
Traceback (most recent call last):
File "/opt/render/project/src/algorithms_keeper/parser/python_parser.py", line 146, in parse
reports = lint_file(
^^^^^^^^^^
libcst._exceptions.ParserSyntaxError: Syntax Error @ 358:1.
parser error: error at 359:0: expected INDENT
# lstm.test()
^
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neural_network/lstm.py
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| self.char_to_idx = {c: i for i, c in enumerate(self.chars)} | ||
| self.idx_to_char = {i: c for i, c in enumerate(self.chars)} | ||
|
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||
| self.train_X, self.train_y = self.data[:-1], self.data[1:] |
There was a problem hiding this comment.
Variable and function names should follow the snake_case naming convention. Please update the following name accordingly: train_X
| self.initialize_weights() | ||
|
|
||
| ##### Helper Functions ##### | ||
| def one_hot_encode(self, char: str) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function one_hot_encode
| vector[self.char_to_idx[char]] = 1 | ||
| return vector | ||
|
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||
| def initialize_weights(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function initialize_weights
| self.wy = self.init_weights(self.hidden_dim, self.char_size) | ||
| self.by = np.zeros((self.char_size, 1)) | ||
|
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| def init_weights(self, input_dim: int, output_dim: int) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function init_weights
neural_network/lstm.py
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| ) | ||
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| ##### Activation Functions ##### | ||
| def sigmoid(self, x: np.ndarray, derivative: bool = False) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function sigmoid
Please provide descriptive name for the parameter: x
neural_network/lstm.py
Outdated
| self.input_gates = {} | ||
| self.outputs = {} | ||
|
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||
| def forward(self, inputs: list) -> list: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function forward
neural_network/lstm.py
Outdated
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| return outputs | ||
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| def backward(self, errors: list, inputs: list) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function backward
| ): | ||
| param -= self.lr * grad | ||
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| def train(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function train
neural_network/lstm.py
Outdated
| # Backward pass and weight updates | ||
| self.backward(errors, inputs) | ||
|
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||
| def predict(self, inputs: list) -> str: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function predict
neural_network/lstm.py
Outdated
| output = self.forward(inputs)[-1] | ||
| return self.idx_to_char[np.argmax(self.softmax(output))] | ||
|
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||
| def test(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function test
There was a problem hiding this comment.
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neural_network/lstm.py
Outdated
| self.char_to_idx = {c: i for i, c in enumerate(self.chars)} | ||
| self.idx_to_char = dict(enumerate(self.chars)) | ||
|
|
||
| self.train_X, self.train_y = self.data[:-1], self.data[1:] |
There was a problem hiding this comment.
Variable and function names should follow the snake_case naming convention. Please update the following name accordingly: train_X
| self.initialize_weights() | ||
|
|
||
| ##### Helper Functions ##### | ||
| def one_hot_encode(self, char: str) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function one_hot_encode
| vector[self.char_to_idx[char]] = 1 | ||
| return vector | ||
|
|
||
| def initialize_weights(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function initialize_weights
neural_network/lstm.py
Outdated
| self.wy = self.init_weights(self.hidden_dim, self.char_size, rng) | ||
| self.by = np.zeros((self.char_size, 1)) | ||
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| def init_weights( |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function init_weights
neural_network/lstm.py
Outdated
| ) | ||
|
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| ##### Activation Functions ##### | ||
| def sigmoid(self, x: np.ndarray, derivative: bool = False) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function sigmoid
Please provide descriptive name for the parameter: x
neural_network/lstm.py
Outdated
| return exp_x / exp_x.sum(axis=0) | ||
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| ##### LSTM Network Methods ##### | ||
| def reset(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function reset
neural_network/lstm.py
Outdated
| self.input_gates = {} | ||
| self.outputs = {} | ||
|
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| def forward(self, inputs: list) -> list: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function forward
neural_network/lstm.py
Outdated
|
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| return outputs | ||
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| def backward(self, errors: list, inputs: list) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function backward
| self.wy += d_wy * self.lr | ||
| self.by += d_by * self.lr | ||
|
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||
| def train(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function train
neural_network/lstm.py
Outdated
|
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| self.backward(errors, self.concat_inputs) | ||
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| def test(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function test
There was a problem hiding this comment.
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neural_network/lstm.py
Outdated
| self.char_to_idx = {c: i for i, c in enumerate(self.chars)} | ||
| self.idx_to_char = dict(enumerate(self.chars)) | ||
|
|
||
| self.train_X, self.train_y = self.data[:-1], self.data[1:] |
There was a problem hiding this comment.
Variable and function names should follow the snake_case naming convention. Please update the following name accordingly: train_X
| self.initialize_weights() | ||
|
|
||
| ##### Helper Functions ##### | ||
| def one_hot_encode(self, char: str) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function one_hot_encode
| vector[self.char_to_idx[char]] = 1 | ||
| return vector | ||
|
|
||
| def initialize_weights(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function initialize_weights
neural_network/lstm.py
Outdated
| self.wy = self.init_weights(self.hidden_dim, self.char_size) | ||
| self.by = np.zeros((self.char_size, 1)) | ||
|
|
||
| def init_weights( |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function init_weights
neural_network/lstm.py
Outdated
| ) | ||
|
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||
| ##### Activation Functions ##### | ||
| def sigmoid(self, x: np.ndarray, derivative: bool = False) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function sigmoid
Please provide descriptive name for the parameter: x
neural_network/lstm.py
Outdated
| return exp_x / exp_x.sum(axis=0) | ||
|
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||
| ##### LSTM Network Methods ##### | ||
| def reset(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function reset
neural_network/lstm.py
Outdated
| self.input_gates = {} | ||
| self.outputs = {} | ||
|
|
||
| def forward(self, inputs: list) -> list: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function forward
neural_network/lstm.py
Outdated
|
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| return outputs | ||
|
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| def backward(self, errors: list, inputs: list) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function backward
| self.wy += d_wy * self.lr | ||
| self.by += d_by * self.lr | ||
|
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||
| def train(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function train
neural_network/lstm.py
Outdated
|
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| self.backward(errors, self.concat_inputs) | ||
|
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||
| def test(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function test
There was a problem hiding this comment.
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@algorithms-keeper reviewto trigger the checks for only added pull request files@algorithms-keeper review-allto trigger the checks for all the pull request files, including the modified files. As we cannot post review comments on lines not part of the diff, this command will post all the messages in one comment.NOTE: Commands are in beta and so this feature is restricted only to a member or owner of the organization.
|
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| self.initialize_weights() | ||
|
|
||
| def one_hot_encode(self, char: str) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function one_hot_encode
| vector[self.char_to_idx[char]] = 1 | ||
| return vector | ||
|
|
||
| def initialize_weights(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function initialize_weights
| self.wy: np.ndarray = self.init_weights(self.hidden_dim, self.char_size) | ||
| self.by: np.ndarray = np.zeros((self.char_size, 1)) | ||
|
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| def init_weights(self, input_dim: int, output_dim: int) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function init_weights
neural_network/lstm.py
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| 6 / (input_dim + output_dim) | ||
| ) | ||
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| def sigmoid(self, x: np.ndarray, derivative: bool = False) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function sigmoid
Please provide descriptive name for the parameter: x
neural_network/lstm.py
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| return x * (1 - x) | ||
| return 1 / (1 + np.exp(-x)) | ||
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| def tanh(self, x: np.ndarray, derivative: bool = False) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function tanh
Please provide descriptive name for the parameter: x
neural_network/lstm.py
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| exp_x = np.exp(x - np.max(x)) | ||
| return exp_x / exp_x.sum(axis=0) | ||
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| def reset(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function reset
neural_network/lstm.py
Outdated
| self.input_gates = {} | ||
| self.outputs = {} | ||
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| def forward(self, inputs: list[np.ndarray]) -> list[np.ndarray]: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function forward
neural_network/lstm.py
Outdated
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| return outputs | ||
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| def backward(self, errors: list[np.ndarray], inputs: list[np.ndarray]) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function backward
| self.wy += d_wy * self.lr | ||
| self.by += d_by * self.lr | ||
|
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| def train(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function train
neural_network/lstm.py
Outdated
|
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| self.backward(errors, inputs) | ||
|
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| def test(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function test
There was a problem hiding this comment.
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|
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| self.initialize_weights() | ||
|
|
||
| def one_hot_encode(self, char: str) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function one_hot_encode
| vector[self.char_to_idx[char]] = 1 | ||
| return vector | ||
|
|
||
| def initialize_weights(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function initialize_weights
| self.wy: np.ndarray = self.init_weights(self.hidden_dim, self.char_size) | ||
| self.by: np.ndarray = np.zeros((self.char_size, 1)) | ||
|
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| def init_weights(self, input_dim: int, output_dim: int) -> np.ndarray: |
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As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function init_weights
neural_network/lstm.py
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| 6 / (input_dim + output_dim) | ||
| ) | ||
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| def sigmoid(self, x: np.ndarray, derivative: bool = False) -> np.ndarray: |
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As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function sigmoid
Please provide descriptive name for the parameter: x
neural_network/lstm.py
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| return x * (1 - x) | ||
| return 1 / (1 + np.exp(-x)) | ||
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| def tanh(self, x: np.ndarray, derivative: bool = False) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function tanh
Please provide descriptive name for the parameter: x
neural_network/lstm.py
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| exp_x = np.exp(x - np.max(x)) | ||
| return exp_x / exp_x.sum(axis=0) | ||
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| def reset(self) -> None: |
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neural_network/lstm.py
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| self.input_gates = {} | ||
| self.outputs = {} | ||
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| def forward(self, inputs: list[np.ndarray]) -> list[np.ndarray]: |
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neural_network/lstm.py
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| return outputs | ||
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| def backward(self, errors: list[np.ndarray], inputs: list[np.ndarray]) -> None: |
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As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function backward
| self.wy += d_wy * self.lr | ||
| self.by += d_by * self.lr | ||
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| def train(self) -> None: |
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As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function train
neural_network/lstm.py
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| self.backward(errors, inputs) | ||
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| def test(self) -> None: |
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As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function test
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| self.initialize_weights() | ||
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| def one_hot_encode(self, char: str) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function one_hot_encode
| vector[self.char_to_idx[char]] = 1 | ||
| return vector | ||
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| def initialize_weights(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function initialize_weights
| self.wy: np.ndarray = self.init_weights(self.hidden_dim, self.char_size) | ||
| self.by: np.ndarray = np.zeros((self.char_size, 1)) | ||
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| def init_weights(self, input_dim: int, output_dim: int) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function init_weights
neural_network/lstm.py
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| 6 / (input_dim + output_dim) | ||
| ) | ||
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| def sigmoid(self, x: np.ndarray, derivative: bool = False) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function sigmoid
Please provide descriptive name for the parameter: x
neural_network/lstm.py
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| return x * (1 - x) | ||
| return 1 / (1 + np.exp(-x)) | ||
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| def tanh(self, x: np.ndarray, derivative: bool = False) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function tanh
Please provide descriptive name for the parameter: x
neural_network/lstm.py
Outdated
| exp_x = np.exp(x - np.max(x)) | ||
| return exp_x / exp_x.sum(axis=0) | ||
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| def reset(self) -> None: |
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As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function reset
neural_network/lstm.py
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| self.input_gates = {} | ||
| self.outputs = {} | ||
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| def forward(self, inputs: list[np.ndarray]) -> list[np.ndarray]: |
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As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function forward
neural_network/lstm.py
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| return outputs | ||
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| def backward(self, errors: list[np.ndarray], inputs: list[np.ndarray]) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function backward
| self.wy += d_wy * self.lr | ||
| self.by += d_by * self.lr | ||
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| def train(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function train
neural_network/lstm.py
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| self.backward(errors, inputs) | ||
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| def test(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function test
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| self.initialize_weights() | ||
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| def one_hot_encode(self, char: str) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function one_hot_encode
| vector[self.char_to_index[char]] = 1 | ||
| return vector | ||
|
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| def initialize_weights(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function initialize_weights
| ) | ||
| self.output_layer_bias: np.ndarray = np.zeros((self.vocabulary_size, 1)) | ||
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| def init_weights(self, input_dim: int, output_dim: int) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function init_weights
neural_network/lstm.py
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| 6 / (input_dim + output_dim) | ||
| ) | ||
|
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| def sigmoid(self, x: np.ndarray, derivative: bool = False) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function sigmoid
Please provide descriptive name for the parameter: x
neural_network/lstm.py
Outdated
| return x * (1 - x) | ||
| return 1 / (1 + np.exp(-x)) | ||
|
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| def tanh(self, x: np.ndarray, derivative: bool = False) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function tanh
Please provide descriptive name for the parameter: x
neural_network/lstm.py
Outdated
| return 1 - x**2 | ||
| return np.tanh(x) | ||
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| def softmax(self, x: np.ndarray) -> np.ndarray: |
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As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function softmax
Please provide descriptive name for the parameter: x
| exp_x = np.exp(x - np.max(x)) | ||
| return exp_x / exp_x.sum(axis=0) | ||
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| def reset_network_state(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function reset_network_state
| self.output_gate_activations = {} | ||
| self.network_outputs = {} | ||
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| def forward_pass(self, inputs: list[np.ndarray]) -> list[np.ndarray]: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function forward_pass
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| return outputs | ||
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| def backward_pass(self, errors: list[np.ndarray], inputs: list[np.ndarray]) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function backward_pass
neural_network/lstm.py
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| return output | ||
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| def test_lstm_workflow(): |
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Please provide return type hint for the function: test_lstm_workflow. If the function does not return a value, please provide the type hint as: def function() -> None:
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| self.initialize_weights() | ||
|
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| def one_hot_encode(self, char: str) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function one_hot_encode
| vector[self.char_to_index[char]] = 1 | ||
| return vector | ||
|
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| def initialize_weights(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function initialize_weights
| ) | ||
| self.output_layer_bias: np.ndarray = np.zeros((self.vocabulary_size, 1)) | ||
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| def init_weights(self, input_dim: int, output_dim: int) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function init_weights
neural_network/lstm.py
Outdated
| 6 / (input_dim + output_dim) | ||
| ) | ||
|
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| def sigmoid(self, x: np.ndarray, derivative: bool = False) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function sigmoid
Please provide descriptive name for the parameter: x
neural_network/lstm.py
Outdated
| return x * (1 - x) | ||
| return 1 / (1 + np.exp(-x)) | ||
|
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| def tanh(self, x: np.ndarray, derivative: bool = False) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function tanh
Please provide descriptive name for the parameter: x
| exp_x = np.exp(x - np.max(x)) | ||
| return exp_x / exp_x.sum(axis=0) | ||
|
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| def reset_network_state(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function reset_network_state
| self.output_gate_activations = {} | ||
| self.network_outputs = {} | ||
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| def forward_pass(self, inputs: list[np.ndarray]) -> list[np.ndarray]: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function forward_pass
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| return outputs | ||
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| def backward_pass(self, errors: list[np.ndarray], inputs: list[np.ndarray]) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function backward_pass
| self.output_layer_weights += d_output_layer_weights * self.learning_rate | ||
| self.output_layer_bias += d_output_layer_bias * self.learning_rate | ||
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| def train(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function train
neural_network/lstm.py
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| self.backward_pass(errors, inputs) | ||
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| def test(self): |
There was a problem hiding this comment.
Please provide return type hint for the function: test. If the function does not return a value, please provide the type hint as: def function() -> None:
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function test
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| ) | ||
| self.output_layer_bias = np.zeros((self.vocabulary_size, 1)) | ||
|
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| def init_weights(self, input_dim: int, output_dim: int) -> np.ndarray: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function init_weights
neural_network/lstm.py
Outdated
| 6 / (input_dim + output_dim) | ||
| ) | ||
|
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| def sigmoid(self, x: np.ndarray, derivative: bool = False) -> np.ndarray: |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: x
neural_network/lstm.py
Outdated
| return x * (1 - x) | ||
| return 1 / (1 + np.exp(-x)) | ||
|
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| def tanh(self, x: np.ndarray, derivative: bool = False) -> np.ndarray: |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: x
neural_network/lstm.py
Outdated
| return 1 - x**2 | ||
| return np.tanh(x) | ||
|
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| def softmax(self, x: np.ndarray) -> np.ndarray: |
There was a problem hiding this comment.
Please provide descriptive name for the parameter: x
| self.output_gate_activations = {} | ||
| self.network_outputs = {} | ||
|
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| def forward_pass(self, inputs: list[np.ndarray]) -> list[np.ndarray]: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function forward_pass
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| return outputs | ||
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| def backward_pass(self, errors: list[np.ndarray], inputs: list[np.ndarray]) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function backward_pass
| self.output_layer_weights += d_output_layer_weights * self.learning_rate | ||
| self.output_layer_bias += d_output_layer_bias * self.learning_rate | ||
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| def train(self) -> None: |
There was a problem hiding this comment.
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function train
neural_network/lstm.py
Outdated
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| self.backward_pass(errors, inputs) | ||
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| def test(self): |
There was a problem hiding this comment.
Please provide return type hint for the function: test. If the function does not return a value, please provide the type hint as: def function() -> None:
As there is no test file in this pull request nor any test function or class in the file neural_network/lstm.py, please provide doctest for the function test
…names in sigmoid function from x to input array
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