Hi, In minitorch, inappropriate dependency versioning constraints can cause risks.
Below are the dependencies and version constraints that the project is using
numpy==1.19.1
numba==0.49
pytest==6.0.1
pytest-env
pytest-runner==5.2
hypothesis==4.38
flake8==3.8.3
black==19.10b0
colorama==0.4.3
pep8-naming==0.11.1
darglint==1.8.0
tbb
The version constraint == will introduce the risk of dependency conflicts because the scope of dependencies is too strict.
The version constraint No Upper Bound and * will introduce the risk of the missing API Error because the latest version of the dependencies may remove some APIs.
After further analysis, in this project,
The version constraint of dependency numpy can be changed to >=1.8.0,<=1.23.0rc3.
The version constraint of dependency hypothesis can be changed to >=5.19.0,<=6.47.3.
The above modification suggestions can reduce the dependency conflicts as much as possible,
and introduce the latest version as much as possible without calling Error in the projects.
The invocation of the current project includes all the following methods.
The calling methods from the numpy
numpy.testing.assert_allclose
The calling methods from the hypothesis
hypothesis.strategies.permutations
random.random
hypothesis.strategies.lists
hypothesis.strategies.integers
hypothesis.strategies.floats
The calling methods from the all methods
cls.variable
Context
minitorch.TensorData
range
self.conv_and_pool
self.backend.LT.apply
self.backend.Neg.apply
threadsperblock.blockspergrid.f
minitorch.fast_ops.tensor_reduce
shape
self.model.forward
minitorch.fast_ops.tensor_reduce.parallel_diagnostics
RParam
run_mnist_multiclass.ImageTrain.train
grad_output.permute
networkx.MultiDiGraph.add_edge
col1.empty
mul_reduce
run_sentiment.SentenceSentimentTrain.train
col2.slider
self.SentimentCNN.super.__init__
ctx.save_for_backward
torch.tensor.float
random.seed
numpy.vstack
super.__setattr__
tensor_data.shape_broadcast
eval
loss.view.backward
SentenceSentimentTrain
CNNSentimentKim
TensorTrain
self.backend.ReLU.apply
numpy.testing.assert_allclose
minitorch.logsoftmax
B.A.sum
streamlit.empty.write
Network2.forward
cls.forward
embeddings.permute
col1.text_input
int.i.i.i.np.array.astype.str.replace.replace.replace
streamlit.empty
int
child_lines.append
self.backend.View.apply
stack.append
minitorch.tensor.sigmoid
steps.append
minitorch.operators.prod
streamlit.empty.progress
self.dropout
MyModule.named_parameters
embeds.permute
model.forward
model.train
col3.number_input
plot_out
self._ensure_tensor
y.shape.prob.log.sum.view
math.exp
tensor_ops.zip
id_map
model.eval
hypothesis.settings.load_profile
HIDDEN.TensorTrain.train
Network
self.linear
col1.number_input
datasets.xor
minitorch.tensor.type_
y.append
datasets.load_dataset
x.self.linear2.sigmoid
get_image_id
self.backend.Sigmoid.apply
neg_map
SentenceSentimentTrain.train
self.backend.Permute.apply
make_tensor_backend
show_tensor.tensor_figure
tensor_ops.matrix_multiply
st_select_index
tensor_ops.map
self.indices
streamlit.markdown
criterion
minitorch.avgpool2d
float
embeddings.GloveEmbedding
History
hypothesis.strategies.integers
get_train
st_eval_error_message.reshape
add_reduce
plotly.graph_objects.Figure.update_layout
make_mnist
select_fn.keys
probs.log.sum.reshape
make_scatters
minitorch.is_constant
streamlit.markdown.markdown
streamlit.beta_columns
draw.permute
prob.log
b.a.is_close.all
y.shape.loss.sum.view.backward
grad_weight.permute.tuple
random.shuffle
tensor_conv2d
st_eval_error_message
model.out.to_numpy
vals1.f.sum
a._new
df.append
minitorch.Tensor.make
X.torch.tensor.self.model.forward.detach
Tensor
self.zeros
graph_builder.GraphBuilder.run
streamlit.number_input
numpy.array
interface.streamlit_utils.get_img_tag
minitorch.rand.sum
mat.transpose
sorted
tensor_zip
data.X.torch.tensor.model.forward.view
box_adder
self.bias.value.view
TrainCls
plot
out.view.view
transpose
treduce
add_one_box
plot_tensor.add_annotation
weight.permute
numba.cuda.is_available
streamlit.sidebar.markdown
f.backward
ob.append
b.append
tuple
dict
range.append
n.__dict__.items
ys.append
streamlit.write
streamlit.slider
TorchTrain
criterion.backward
scalar
numpy.random.RandomState.rand
weight.permute.tuple
abs
streamlit.empty.dataframe
pandas.DataFrame
globals
run_sentiment.encode_sentiment_data
super
torch.cat
minitorch.rand.type_
get_dataset
W.H.BATCH.x.view.model.forward.view
make_oned
numba.njit
h.self.layer3.forward.sigmoid
plot_tensor.show
b.a.is_close.all.item
self.__dict__.values
self.bias.append
GraphBuilder.run
GraphBuilder.run.add_edge
load_data
self._tensor.to_string
pred.y.sum
streamlit.subheader
tensor_data.TensorData.shape_broadcast
streamlit.cache
random.random
streamlit.plotly_chart
hypothesis.settings.register_profile
a.contiguous.view
streamlit.set_page_config
Mul.apply
a._tensor.permute
GPUBackend.FastTensorBackend.args.BACKEND.HIDDEN.FastTrain.train
predictions_dataframe
pandas.DataFrame.apply
int.i.i.i.np.array.astype.str.replace
tzip
streamlit.selectbox
tensor_conv1d
minitorch.MathTest._tests
plotly.graph_objects.Figure.add_trace
torch.nn.Parameter
a.append
join
numba.cuda.to_device
input.permute.tuple
plotly.graph_objects.Layout
torch.nn.BCELoss
hypothesis.strategies.lists
GraphBuilder
torch.tensor.max
datasets_map.keys
minitorch.fast_ops.tensor_map
minitorch.Conv2dFun.apply
in_size.batch.x.view.self.out_size.in_size.self.weights.value.view.sum
name.model.graph.plot_out.show
val_x.numpy.array.reshape
input.tuple
streamlit.text_area
st_visualize_tensor
loss.sum.view
y.shape.loss.sum
min
TrainCls.train
a.is_close
minitorch.index_to_position
visdom.Visdom.images
Network2
self._tensor.to_cuda_
self.zero_derivative_
self.layer1.forward
fn
self.backend.Exp.apply
to_index
PAGES.keys
plot_tensor
torch.nn.Conv1d
self.forward
model.squeeze
dim.cols.write
argparse.ArgumentParser.add_argument
tensor_matrix_multiply
y
self.out_size.in_size.self.weights.value.view.in_size.batch.x.view.view
b.contiguous.view.tuple
minitorch.to_index
ScalarTrain
streamlit.beta_expander
streamlit.table
y.shape.loss.sum.view
Network2.parameters
map
minitorch.Tensor
y.shape.prob.log.sum
construct_tensor
x.x.map.list.np.array.ravel
zip
numpy.hstack
plotly.graph_objects.Figure
self.sum
argparse.ArgumentParser.parse_args
Conv2d
visdom.Visdom
self.backend.Copy.apply
col2.button
a.tuple
torch.nn.Dropout
col2.text_input
tensor.Tensor
run_mnist_multiclass.ImageTrain
self.backend.All.apply
self.weights.append
project.run_sentiment.encode_sentiment_data
streamlit.progress.progress
out.tuple
torch.nn.ModuleList
out.view.to_cuda_
threadsperblock.blockspergrid.tensor_matrix_multiply
graph_builder.build_tensor_expression
cur.is_leaf
set
y2.out.get_data.sum
make_pts
random.randint
streamlit.button
predictions_array.append
tensor.Tensor.make.requires_grad_
self.get
X.append
graph_builder.build_expression
bool
minitorch.datasets
minitorch.fast_ops.tensor_map.parallel_diagnostics
self.backend._id_map
index_to_position
load_glue_dataset
show_expression_interface.render_show_expression
self.is_leaf
enumerate
vals2.f.sum
grad_weight.permute.permute
train
max
conv
TrainCls.run_one
model.parameters
exec
minitorch.fast_ops.tensor_zip
str
minitorch.Parameter
p.grad.zero_
tmm.parallel_diagnostics
torch.nn.Sigmoid
MMLinear
a.contiguous.view.contiguous
zero
y.copy
h.self.layer2.forward.relu
y.shape.prob.sum
project.interface.streamlit_utils.render_function
tensor_ops.reduce
flatten
torch.nn.Linear
plotly.express.imshow
ImageTrain.train
backpropagate
list
graph_builder.GraphBuilder
HIDDEN.ScalarTrain.train
raw_vals.append
project.run_sentiment.CNNSentimentKim
coords.append
losses.append
self._tensor.set
grad_output.zeros
st_visualize_storage
p.update
super.backward
embeddings_lookup.emb
X.self.model.forward.view
plot_tensor.update_layout
self.layer2.forward
B.A.sum.backward
G.nx.nx_pydot.to_pydot.to_string
end.self.layer3.forward.sigmoid
minitorch.operators.sigmoid
draw
minitorch.tensor.view
self.contiguous
tensor.permute
self.backend.Log.apply
math.cos
out.view.tuple
in_size.batch.x.view.self.out_size.in_size.self.weights.value.view.sum.view
streamlit.sidebar.radio
super.__init__
oa.append
self.backend.MatMul.apply
grad_output.permute.tuple
tensor_interface.render_tensor_sandbox
Conv1d
x.self.conv1.relu
math_interface.render_math_sandbox
streamlit.checkbox
input.zeros
self.index
Ze.extend
n_cols.idx.cols.number_input
Xs.append
central_difference
Tensor.make._type_
x
streamlit.text_input
self.conv3
model.zero_grad
x.x1.map.list.np.array.ravel
unwrap_tuple
model
Tensor.make
FastTrain
run_mnist_multiclass.make_mnist
probs.log.sum.view
i.i.i.np.array.astype
tensor_reduce
plot_tensor.add_trace
self.model.parameters
Parameter
self.backend.Mul.apply
self._tensor.tuple
x.requires_grad_
X.self.model.forward.view.get_data
log_fn
weights.append
self.add_parameter
minitorch.SGD.zero_grad
x.self.conv3.relu
grad_output.tuple
_tensor
data.N.loss.backward
torch.rand
max_reduce
interface.train.render_train_interface
validation_accuracy.append
minitorch.SGD
self.backend.Sum.apply
model_output.to_numpy
minitorch.MathTestVariable._tests
self.fc
shapes
torch.tensor
data.N.loss.sum.view.backward
zero._type_
minitorch.matmul
Linear
minitorch.make_tensor_backend
inspect.getsource
page
self.out_size.in_size.self.weights.value.view.in_size.batch.x.view.minitorch.matmul.view
autodiff.History
loss.reshape.item
queue.append
a.contiguous
tmm
MyModule
streamlit.empty.plotly_chart
repr
x.self.layer1.forward.relu
threadsperblock.blockspergrid.jit_sum_practice
operators.log
x.zero_grad_
isinstance
tensor_data
scalar.backward
b.tuple
self.backend.IsClose.apply
threadsperblock.blockspergrid.jit_mm_practice
data.N.loss.sum
f.sum
self.conv2
numpy.ones
len
a.zeros.tuple
self.value.requires_grad_
time.time
set.add
a.contiguous.view.tuple
datasets.split
fast_ops.FastOps.reduce
col1.selectbox.datasets_map
networkx.nx_pydot.to_pydot
mnist.MNIST.load_training
self.linear1
numpy.round
scalars
minitorch.tensor.requires_grad_
operators.log_back
self.backend.EQ.apply
probs.log.sum
b.contiguous.view.contiguous
plotly.graph_objects.Contour
x.sigmoid.view
val_ys.append
torch.nn.functional.relu
minitorch.zeros
streamlit.empty.markdown
inv_back_zip
networkx.MultiDiGraph.add_node
numba.cuda.is_cuda_array
values.append
numba.cuda.jit
print
minitorch.fast_ops.tensor_zip.parallel_diagnostics
minitorch.make_tensor_functions
a.contiguous.view.zeros
minitorch.max
hasattr
BATCH.x.view.model.forward.view
strides_from_shape
operators.prod
argparse.ArgumentParser
GraphBuilder.run.add_node
self.layer3.forward
Ye.extend
add_zip
y.out.sum
streamlit.text
self.backend._add_reduce
minitorch.operators.is_close
minitorch.rand
minitorch.prod
G.nx.nx_pydot.to_pydot.create_svg
make_pts.append
reversed
plotly.graph_objects.Mesh3d
a._tensor.is_contiguous
sentence.split
TrainCls.run_many
join.pop
Inv.apply
int.i.i.i.np.array.astype.str.replace.replace
out.sum.backward
val_losses.append
math.sin
get_predictions_array
torch.optim.Adam.step
s_.split
numpy.random.RandomState
probs.log
input.zeros.tuple
self.backend.Add.apply
col1.empty.button
criterion.item
tensor_map
minitorch.conv2d
prob.log.sum
minitorch.SGD.step
self.sig
interface.plots.plot_out
ImageTrain
streamlit.error
self.linear2
weight.tuple
train.model.named_parameters
model.mid.to_numpy
cls.data
streamlit.selectbox.select_fn
SentimentCNN
torch.optim.Adam
input.permute
self._tensor.get
mnist.MNIST
Xe.extend
NotImplementedError
encode_sentiment_data
encode_sentences
interface.streamlit_utils.render_function
HIDDEN.TorchTrain.train
type
make_scatters.append
a.zeros
list.append
y.shape.prob.sum.view
i.self.weights.append
col1.selectbox
self.conv1
minitorch.Scalar
grad_central_difference
construct_whole_box
show_tensor.tensor_figure.update_layout
streamlit.header
Graph
run_sentiment.SentenceSentimentTrain
plotly.graph_objects.Figure.show
format
hypothesis.strategies.permutations
self._modules.items
x.view
data.N.loss.sum.view
datasets.simple
streamlit.progress
tensor.Tensor.make
self.contiguous._tensor._storage.reshape
list.reverse
streamlit.warning
IndexingError
plotly.graph_objects.Scatter
loss.sum.view.backward
col2.number_input
train_accuracy.append
minitorch.tensor
get_accuracy
minitorch.dropout
b.contiguous.view
shape_broadcast
streamlit.graphviz_chart
tensor_data.TensorData
networkx.MultiDiGraph
zeros
layout.append
BATCH.x.view.self.linear1.relu
h.relu
setuptools.setup
minitorch.conv1d
self.weights.value.view
math.log
inv_map
plotly.graph_objects.Surface
f
tmap
self.backend.Inv.apply
x._tensor.sample
v.get_data
x.self.conv2.relu
hypothesis.strategies.floats
self.get_name
pred.y.sum.item
_addindent
@developer
Could please help me check this issue?
May I pull a request to fix it?
Thank you very much.
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