@@ -20,8 +20,8 @@ def generic_evaluator(solver_input: SolverInput, weights: np.ndarray, options: I
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# * Chunking the evaluation
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max_size = options .evaluation_chunk_size
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n_chunks = int (np .ceil (matrix_size / max_size ))
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- chunk_size = int (np .ceil (matrix_size / n_chunks ))
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- for i in range (n_chunks ):
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+ chunk_size = int (np .ceil (grid_size / n_chunks ))
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+ for i in range (n_chunks ): # TODO: It seems the chunking is not properly implemented
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slice_array = slice (i * chunk_size , (i + 1 ) * chunk_size )
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scalar_field_chunk , gx_field_chunk , gy_field_chunk , gz_field_chunk = _eval_on (
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solver_input = solver_input ,
@@ -50,6 +50,7 @@ def generic_evaluator(solver_input: SolverInput, weights: np.ndarray, options: I
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def _eval_on (solver_input , weights , options , slice_array : slice = None ):
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eval_kernel = yield_evaluation_kernel (solver_input , options .kernel_options , slice_array = slice_array )
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scalar_field : np .ndarray = (eval_kernel .T @ weights ).reshape (- 1 )
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+ scalar_field [- 50 :]
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gx_field : Optional [np .ndarray ] = None
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gy_field : Optional [np .ndarray ] = None
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gz_field : Optional [np .ndarray ] = None
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