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ThorbenFroehlking
commited on
Commit
·
f506fb3
1
Parent(s):
c85a5b0
Update
Browse files- .ipynb_checkpoints/app-checkpoint.py +5 -4
- app.py +5 -4
.ipynb_checkpoints/app-checkpoint.py
CHANGED
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@@ -67,7 +67,7 @@ def process_pdb(pdb_id, segment):
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except KeyError:
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return "Invalid Chain ID", None, None
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-
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aa_dict = {
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'ALA': 'A', 'CYS': 'C', 'ASP': 'D', 'GLU': 'E', 'PHE': 'F',
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'GLY': 'G', 'HIS': 'H', 'ILE': 'I', 'LYS': 'K', 'LEU': 'L',
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@@ -77,10 +77,11 @@ def process_pdb(pdb_id, segment):
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}
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# Exclude non-amino acid residues
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-
sequence =
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residue
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if residue.get_resname().strip() in aa_dict
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-
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# Prepare input for model prediction
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input_ids = tokenizer(" ".join(sequence), return_tensors="pt").input_ids.to(device)
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except KeyError:
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return "Invalid Chain ID", None, None
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+
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aa_dict = {
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'ALA': 'A', 'CYS': 'C', 'ASP': 'D', 'GLU': 'E', 'PHE': 'F',
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'GLY': 'G', 'HIS': 'H', 'ILE': 'I', 'LYS': 'K', 'LEU': 'L',
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}
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# Exclude non-amino acid residues
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+
sequence = "".join(
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+
aa_dict[residue.get_resname().strip()]
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+
for residue in chain
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if residue.get_resname().strip() in aa_dict
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+
)
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# Prepare input for model prediction
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input_ids = tokenizer(" ".join(sequence), return_tensors="pt").input_ids.to(device)
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app.py
CHANGED
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@@ -67,7 +67,7 @@ def process_pdb(pdb_id, segment):
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| 67 |
except KeyError:
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return "Invalid Chain ID", None, None
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-
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aa_dict = {
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'ALA': 'A', 'CYS': 'C', 'ASP': 'D', 'GLU': 'E', 'PHE': 'F',
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| 73 |
'GLY': 'G', 'HIS': 'H', 'ILE': 'I', 'LYS': 'K', 'LEU': 'L',
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@@ -77,10 +77,11 @@ def process_pdb(pdb_id, segment):
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}
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# Exclude non-amino acid residues
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-
sequence =
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-
residue
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if residue.get_resname().strip() in aa_dict
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-
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# Prepare input for model prediction
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input_ids = tokenizer(" ".join(sequence), return_tensors="pt").input_ids.to(device)
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except KeyError:
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return "Invalid Chain ID", None, None
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+
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aa_dict = {
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'ALA': 'A', 'CYS': 'C', 'ASP': 'D', 'GLU': 'E', 'PHE': 'F',
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'GLY': 'G', 'HIS': 'H', 'ILE': 'I', 'LYS': 'K', 'LEU': 'L',
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}
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# Exclude non-amino acid residues
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+
sequence = "".join(
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+
aa_dict[residue.get_resname().strip()]
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+
for residue in chain
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if residue.get_resname().strip() in aa_dict
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+
)
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# Prepare input for model prediction
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input_ids = tokenizer(" ".join(sequence), return_tensors="pt").input_ids.to(device)
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