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next field is at offset %zd but %zd expectedArgument '%.200s' has incorrect type (expected %.200s, got %.200s)Cannot convert %.200s to %.200s__%.4s__ returned non-%.4s (type %.200s)value too large to convert to int%.200s.%.200s is not a type object%s.%s size changed, may indicate binary incompatibility%.200s.%.200s has the wrong size, try recompiling%.200s() got an unexpected keyword argument '%.200s'%s() got multiple values for keyword argument '%s'%.200s() keywords must be strings%.200s() takes %.8s %zd positional argument%.1s (%zd given)Big-endian buffer not supported on little-endian compilerBuffer acquisition: Expected '{' after 'T'Cannot handle repeated arrays in format stringDoes not understand character buffer dtype format string ('%c')Expected a dimension of size %zu, got %dExpected a comma in format string, got '%c'Expected %d dimension(s), got %dUnexpected end of format string, expected ')'raise: arg 3 must be a traceback or Noneinstance exception may not have a separate valueraise: exception class must be a subclass of BaseException while calling a Python objectNULL result without error in PyObject_Callsklearn.utils.seq_dataset.SequentialDataset.next'NoneType' object is not iterabletoo many values to unpack (expected %zd)need more than %zd value%.1s to unpack'%.200s' does not have the buffer interfaceBuffer has wrong number of dimensions (expected %d, got %d)Item size of buffer (%zd byte%s) does not match size of '%s' (%zd byte%s)sklearn.utils.seq_dataset.ArrayDataset.__cinit__sklearn.utils.seq_dataset.CSRDataset.__cinit__compiletime version %s of module '%.100s' does not match runtime version %snumpy.core.multiarray failed to import_ARRAY_API is not PyCObject objectmodule compiled against ABI version 0x%x but this version of numpy is 0x%xmodule compiled against API version 0x%x but this version of numpy is 0x%xFATAL: module compiled as unknown endianFATAL: module compiled as little endian, but detected different endianness at runtimeinit sklearn.utils.seq_datasetsklearn.utils.seq_dataset.CSRDatasetA ``SequentialDataset`` backed by a scipy sparse CSR matrix. sklearn.utils.seq_dataset.ArrayDatasetDataset backed by a two-dimensional numpy array.

    The dtype of the numpy array is expected to be ``np.float64`` (double)
    and C-style memory layout.
    sklearn.utils.seq_dataset.SequentialDatasetBase class for datasets with sequential data access. 
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