fix corner cases
Browse files
app.py
CHANGED
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@@ -16,6 +16,12 @@ t2 = torch.arange({n2}).view({dim2})
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"""
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def generate_example(dim1: list, dim2: list):
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n1 = 1
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@@ -58,25 +64,35 @@ def sanitize_dimention(dim):
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return out
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def create_row(dim,is_dim=None,checks=None):
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out = "| "
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n_dim = len(dim)
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for i in range(n_dim):
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return out + "\n"
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@@ -89,20 +105,20 @@ def create_header(n_dim, checks=None):
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return out
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def generate_table(dim1, dim2, checks=None):
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n_dim = len(dim1)
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table = create_header(n_dim, checks)
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# tensor 1
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if not checks :
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table += create_row(dim1)
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else :
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table += create_row(dim1,1,checks)
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# tensor 2
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if not checks :
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table += create_row(dim2)
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else :
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table += create_row(dim2,2,checks)
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return table
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@@ -122,8 +138,6 @@ def alignment_and_fill_with_ones(dim1, dim2):
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return dim1, dim2
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def check_validity(dim1,dim2):
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if len(dim1) < 2:
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return ["WIP"] * len(dim1)
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out = []
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for i in range(len(dim1)-2):
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if dim1[i] == dim2[i]:
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@@ -138,8 +152,9 @@ def check_validity(dim1,dim2):
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return out
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def substitute_ones_with_concat(dim1,dim2):
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dim1[i] = dim2[i] if dim1[i] == 1 else dim1[i]
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dim2[i] = dim1[i] if dim2[i] == 1 else dim2[i]
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return dim1, dim2
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@@ -147,30 +162,63 @@ def substitute_ones_with_concat(dim1,dim2):
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def predict(dim1, dim2):
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dim1 = sanitize_dimention(dim1)
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dim2 = sanitize_dimention(dim2)
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# TODO
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return out
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"""
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matrix_loop = """```python
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out = 0
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for i, j in zip(t1, t2):
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out += i * j
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```
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"""
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def generate_example(dim1: list, dim2: list):
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n1 = 1
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return out
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def create_row(dim,is_dim=None,checks=None,version=1):
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out = "| "
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n_dim = len(dim)
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for i in range(n_dim):
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if version == 1 :
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# infered last dims
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if (is_dim ==1 and i == n_dim-2) or (is_dim ==2 and i ==n_dim-1):
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color = "green"
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out += f"<strong style='color: {color}'> {dim[i]} </strong>| "
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# check every normal dimension
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elif (is_dim ==1 and i != n_dim-1) or (is_dim ==2 and i ==n_dim-1):
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color = "green" if checks[i] == "V" else "red"
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out += f"<strong style='color: {color}'> {dim[i]} </strong>| "
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# checks last 2 dims
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elif (is_dim ==1 and i == n_dim-1) or (is_dim ==2 and i ==n_dim-2):
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color = "blue" if checks[i] == "V" else "yellow"
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out += f"<strong style='color: {color}'> {dim[i]} </strong>| "
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# when using this function without checks
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else :
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out+= f"{dim[i]} | "
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if version == 2 :
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if (is_dim == 1 and i != n_dim-1) :
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out += f"<strong style='color: green'> {dim[i]} </strong>| "
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elif i == n_dim-1 :
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color = "blue" if checks[i] == "V" else "yellow"
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out += f"<strong style='color: {color}'> {dim[i]} </strong>| "
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else :
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out += f"{dim[i]} | "
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return out + "\n"
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return out
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def generate_table(dim1, dim2, checks=None,version=1):
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n_dim = len(dim1)
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table = create_header(n_dim, checks)
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# tensor 1
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if not checks :
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table += create_row(dim1)
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else :
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table += create_row(dim1,1,checks,version)
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# tensor 2
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if not checks :
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table += create_row(dim2)
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else :
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table += create_row(dim2,2,checks,version)
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return table
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return dim1, dim2
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def check_validity(dim1,dim2):
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out = []
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for i in range(len(dim1)-2):
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if dim1[i] == dim2[i]:
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return out
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def substitute_ones_with_concat(dim1,dim2,version = 1):
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n = len(dim1)-2 if version ==1 else len(dim1)-1
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for i in range(n):
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dim1[i] = dim2[i] if dim1[i] == 1 else dim1[i]
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dim2[i] = dim1[i] if dim2[i] == 1 else dim2[i]
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return dim1, dim2
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def predict(dim1, dim2):
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dim1 = sanitize_dimention(dim1)
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dim2 = sanitize_dimention(dim2)
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n1 , n2 = len(dim1) , len(dim2)
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dim1, dim2, out = generate_example(dim1, dim2)
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# TODO
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if n1 >1 and n2 > 1 :
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# Table 1
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dim1, dim2 = alignment_and_fill_with_ones(dim1, dim2)
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table1 = generate_table(dim1, dim2)
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# Table 2
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dim1, dim2 = substitute_ones_with_concat(dim1,dim2)
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table2 = generate_table(dim1, dim2)
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# Table 3
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checks = check_validity(dim1,dim2)
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table3 = generate_table(dim1,dim2,checks)
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out += "\n# Step1 (alignment and pre_append with ones)\n" + table1
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out += "\n# Step2 (susbtitute columns that have 1 with concat)\nexcept for last 2 dimensions\n" + table2
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out += "\n# Step3 (check if matrix multiplication is valid)\n"
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out += "* last dimension of dim1 should equal before last dimension of dim2 (blue or yellow colors)\n"
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out += "* all the other dimensions should be equal to one another (green or red colors)\n\n" + table3
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if "X" not in checks :
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dim1[-1] = dim2[-1]
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out += "\n# Final dimension\n"
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out+="as highlighted in <strong style='color:green'> green </strong> \n\n"
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out+= f"`output.shape = {dim1}`"
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# case single dims
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elif n1 == 1 and n2 == 1 :
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out += "# Single Dimensional Cases\n"
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out += "When both matricies have only single dims they should both have the same number of values in the first dimension\n"
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out += "meaning that `t1.shape == t2.shape`\n"
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out += "the output is a single value, think : \n"
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out += matrix_loop
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else :
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out += "# One of the dimensions is a single dimension\n"
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out += "In this case we need to assert that the last dimension of `t1` "
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out += "is equal to the last dimension of `t2`\n"
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out += "Once the assertion is valid then we get rid of the last dimension and keep the rest\n"
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out += "# Step 1 (alignment and fill with ones)\n"
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dim1, dim2 = alignment_and_fill_with_ones(dim1, dim2)
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table = generate_table(dim1, dim2)
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out += table
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out += "\n# Step2 (susbtitute columns that have 1 with concat)\n"
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out += ""
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dim1, dim2 = substitute_ones_with_concat(dim1,dim2,2)
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checks = ["V"] * (len(dim1)-1)
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if dim1[-1] == dim2[-1] :
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checks.append("V")
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else :
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checks.append("X")
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table = generate_table(dim1, dim2,checks,2)
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out+= table
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if "X" not in checks :
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out += "\n#Final dimension"
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out += "The final dimension is everything colored in <strong style='color:green'> green </strong> \n"
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out += f"\nfinal dimension = `{dim1[:-1]}` "
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return out
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