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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def transform(self, sequences):
 """Apply dimensionality reduction to sequences Parameters sequences: list of array-like, each of shape (n_samples_i, n_features) Sequence data to transform, where n_samples_i in the number of samples in sequence i and n_features is the number of features. Returns ------- sequence_new : list of array-like, each of shape (n_samples_i, n_components) """

        check_iter_of_sequences(sequences)
        transforms = []
        for X in sequences:
            transforms.append(self.partial_transform(X))
        return transforms