def _vector_str(self, indent, summarize, formatter1):
# length includes spaces and comma between elements
element_length = formatter1.width() + 2
elements_per_line = max(
1, int(math.floor((PRINT_OPTS.linewidth - indent) / (element_length)))
)
def _val_formatter(val, formatter1=formatter1):
return formatter1.format(val)
if summarize and self.size(0) > 2 * PRINT_OPTS.edgeitems:
left_values = _try_convert_to_local_tensor(
slice_wrapper(self, [0, PRINT_OPTS.edgeitems, 1])
).tolist()
right_values = _try_convert_to_local_tensor(
slice_wrapper(self, [self.size(0) - PRINT_OPTS.edgeitems, self.size(0), 1])
).tolist()
data = (
[_val_formatter(val) for val in left_values]
+ [" ..."]
+ [_val_formatter(val) for val in right_values]
)
else:
values = _try_convert_to_local_tensor(self).tolist()
data = [_val_formatter(val) for val in values]
data_lines = [
data[i : i + elements_per_line] for i in range(0, len(data), elements_per_line)
]
lines = [", ".join(line) for line in data_lines]
return "[" + ("," + "\n" + " " * (indent + 1)).join(lines) + "]"
def get_summarized_data(self):
dim = self.dim()
if dim == 0:
return self
if dim == 1:
if self.size(0) > 2 * PRINT_OPTS.edgeitems:
return flow.cat(
(
slice_wrapper(self, [0, PRINT_OPTS.edgeitems, 1]),
slice_wrapper(
self, [self.size(0) - PRINT_OPTS.edgeitems, self.size(0), 1]
),
)
)
else:
return self
if self.size(0) > 2 * PRINT_OPTS.edgeitems:
start = [
slice_wrapper(self, [i, i + 1, 1]) for i in range(0, PRINT_OPTS.edgeitems)
]
end = [
slice_wrapper(self, [i, i + 1, 1])
for i in range(self.shape[0] - PRINT_OPTS.edgeitems, self.shape[0])
]
return flow.stack([get_summarized_data(x) for x in (start + end)])
else:
return flow.stack(
[
get_summarized_data(slice_wrapper(self, [i, i + 1, 1]))
for i in range(len(self))
]
)
def _tensor_str_with_formatter(self, indent, summarize, formatter1):
dim = self.dim()
if dim == 0:
return _scalar_str(self, formatter1)
if dim == 1:
return _vector_str(self, indent, summarize, formatter1)
if summarize and self.size(0) > 2 * PRINT_OPTS.edgeitems:
slices = ([
_tensor_str_with_formatter(
slice_wrapper(self, [i, i + 1, 1]),
indent + 1,
summarize,
formatter1,
) for i in range(0, PRINT_OPTS.edgeitems)
] + ["..."] + [
_tensor_str_with_formatter(
slice_wrapper(self, [i, i + 1, 1]),
indent + 1,
summarize,
formatter1,
)
for i in range(self.shape[0] - PRINT_OPTS.edgeitems, self.shape[0])
])
else:
slices = [
_tensor_str_with_formatter(slice_wrapper(self, [i, i + 1, 1]),
indent + 1, summarize, formatter1)
for i in range(0, self.size(0))
]
tensor_str = ("," + "\n" * (dim - 1) + " " * (indent + 1)).join(slices)
return "[" + tensor_str + "]"