Phil 5.7.20

D20

  • Everything is silent again.

GPT-2 Agents

  • Continuing with PGNtoEnglish
    • Building out move text
    • Changing board to a dataframe, since I can display it as a table in pyplot – done!

chessboard

  • Here’s the code for making the chesstable table in pyplot:
    import pandas as pd
    import matplotlib.pyplot as plt
    
    class Chessboard():
        board:pd.DataFrame
        rows:List
        cols:List
    
        def __init__(self):
            self.reset()
    
        def reset(self):
            self.cols = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h']
            self.rows = [8, 7, 6, 5, 4, 3, 2, 1]
            self.board = df = pd.DataFrame(columns=self.cols, index=self.rows)
            for number in self.rows:
                for letter in self.cols:
                    df.at[number, letter] = pieces.NONE.value
    
            self.populate_board()
            self.print_board()
    
        def populate_board(self):
            self.board.at[1, 'a'] = pieces.WHITE_ROOK.value
            self.board.at[1, 'h'] = pieces.WHITE_ROOK.value
            self.board.at[1, 'b'] = pieces.WHITE_KNIGHT.value
            self.board.at[1, 'g'] = pieces.WHITE_KNIGHT.value
            self.board.at[1, 'c'] = pieces.WHITE_BISHOP.value
            self.board.at[1, 'f'] = pieces.WHITE_BISHOP.value
            self.board.at[1, 'd'] = pieces.WHITE_QUEEN.value
            self.board.at[1, 'e'] = pieces.WHITE_KING.value
    
            self.board.at[8, 'a'] = pieces.BLACK_ROOK.value
            self.board.at[8, 'h'] = pieces.BLACK_ROOK.value
            self.board.at[8, 'b'] = pieces.BLACK_KNIGHT.value
            self.board.at[8, 'g'] = pieces.BLACK_KNIGHT.value
            self.board.at[8, 'c'] = pieces.BLACK_BISHOP.value
            self.board.at[8, 'f'] = pieces.BLACK_BISHOP.value
            self.board.at[8, 'd'] = pieces.BLACK_KING.value
            self.board.at[8, 'e'] = pieces.BLACK_QUEEN.value
    
            for letter in self.cols:
                self.board.at[2, letter] = pieces.WHITE_PAWN.value
                self.board.at[7, letter] = pieces.BLACK_PAWN.value
    
        def print_board(self):
            fig, ax = plt.subplots()
    
            # hide axes
            fig.patch.set_visible(False)
            ax.axis('off')
            ax.axis('tight')
    
            ax.table(cellText=self.board.values, colLabels=self.cols, rowLabels=self.rows, loc='center')
    
            fig.tight_layout()
    
            plt.show()

GOES

  • Continuing with the MLP sequence-to-sequence NN
  • Writing
  • Reading
    • Hmm. Just realized that the input vector being defined by the query is a bit problematic. I think I need to define the input vector size and then ensure that the query creates sufficient points. Fixed. It now stores the model with the specified input vector size:

model_name

  • And here’s the loaded model in newly-retrieved data:
  • Here’s the model learning two waveforms. Went from 400×2 neurons to 3200×2:
  • Combining with GAN
    • Subtract the sin from the noisy_sin to get the moise and train on that
  • Start writing paper? What are other venues beyond GVSETS?
  • 2:00 status meeting

JuryRoom

  • 3:30 Meeting
  • 6:00 Meeting

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