unhashable type: 'list' #84

Open
Open
unhashable type: 'list'#84

Description

@Snehal-V2
Snehal-V2
opened on Dec 30, 2024

HI,im trying to run input.yaml file through pacemaker but im getting this error. I dont know how to use it.
cutoff: 7.0 # cutoff for neighbour list construction
seed: 42 # random seed

#################################################################

Metadata section

#################################################################
metadata:
origin: "Automatically generated input"

#################################################################

Potential definition section

#################################################################
potential:
deltaSplineBins: 0.001
elements: ['S', 'S', 'W', 'W']

embeddings:
ALL: {
npot: 'FinnisSinclairShiftedScaled',
fs_parameters: [ 1, 1, 1, 0.5 ],
ndensity: 2,
}

bonds:
ALL: {
radbase: SBessel,
radparameters: [ 5.25 ],
rcut: 7.0,
dcut: 0.01,
NameOfCutoffFunction: cos,
}

functions:
number_of_functions_per_element: 700
UNARY: { nradmax_by_orders: [ 15, 6, 4, 3, 2, 2 ], lmax_by_orders: [ 0 , 3, 3, 2, 2, 1 ]}
BINARY: { nradmax_by_orders: [ 15, 6, 3, 2, 2, 1 ], lmax_by_orders: [ 0 , 3, 2, 1, 1, 0 ]}
TERNARY: { nradmax_by_orders: [ 15, 3, 3, 2, 1 ], lmax_by_orders: [ 0 , 2, 2, 1, 1 ], }
ALL: { nradmax_by_orders: [ 15, 3, 2, 1, 1 ], lmax_by_orders: [ 0 , 2, 2, 1, 1 ] }

#################################################################

Dataset specification section

#################################################################
data:
filename: md_fixed.pckl.gzip # force to read reference pickled dataframe from given file

aug_factor: 1e-4 # common prefactor for weights of augmented structures

reference_energy: auto

#################################################################

Fit specification section

#################################################################
fit:
loss: { kappa: 0.3, L1_coeffs: 1e-8, L2_coeffs: 1e-8}

if kappa: auto, then it will be determined from the variation of energy per atom and forces norms in train set

weighting: { type: EnergyBasedWeightingPolicy, DElow: 1.0, DEup: 10.0, DFup: 50.0, DE: 1.0, DF: 1.0, wlow: 0.75, energy: convex_hull, reftype: all,seed: 42}

optimizer: BFGS # or L-BFGS-B

maximum number of minimize iterations

maxiter: 2000

additional options for scipy.minimize

options: {maxcor: 100}

Automatically find the smallest interatomic distance in dataset and set inner cutoff for ZBL to it

repulsion: auto

ladder_step: 100

ladder_type: power_order

Early stopping

min_relative_train_loss_per_iter: 5e-5

min_relative_test_loss_per_iter: 1e-5

early_stopping_patience: 200

#################################################################

Backend specification section

#################################################################
backend:
evaluator: tensorpot
batch_size: 100
display_step: 50

Metadata

Metadata

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      , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
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}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

      Skip to content
      unhashable type: 'list' #84
      Open
      Open
      unhashable type: 'list'#84
      Description
      @Snehal-V2
      Snehal-V2
      opened on Dec 30, 2024
      HI,im trying to run input.yaml file through pacemaker but im getting this error. I dont know how to use it.
      
cutoff: 7.0 # cutoff for neighbour list construction
      
seed: 42 # random seed
      #################################################################
      Metadata section
      #################################################################
      
metadata:
      
origin: "Automatically generated input"
      #################################################################
      Potential definition section
      #################################################################
      
potential:
      
deltaSplineBins: 0.001
      
elements: ['S', 'S', 'W', 'W']
      embeddings:
      
ALL: {
      
npot: 'FinnisSinclairShiftedScaled',
      
fs_parameters: [ 1, 1, 1, 0.5 ],
      
ndensity: 2,
      
}
      bonds:
      
ALL: {
      
radbase: SBessel,
      
radparameters: [ 5.25 ],
      
rcut: 7.0,
      
dcut: 0.01,
      
NameOfCutoffFunction: cos,
      
}
      functions:
      
number_of_functions_per_element: 700
      
UNARY: { nradmax_by_orders: [ 15, 6, 4, 3, 2, 2 ], lmax_by_orders: [ 0 , 3, 3, 2, 2, 1 ]}
      
BINARY: { nradmax_by_orders: [ 15, 6, 3, 2, 2, 1 ], lmax_by_orders: [ 0 , 3, 2, 1, 1, 0 ]}
      
TERNARY: { nradmax_by_orders: [ 15, 3, 3, 2, 1 ], lmax_by_orders: [ 0 , 2, 2, 1, 1 ], }
      
ALL: { nradmax_by_orders: [ 15, 3, 2, 1, 1 ], lmax_by_orders: [ 0 , 2, 2, 1, 1 ] }
      #################################################################
      Dataset specification section
      #################################################################
      
data:
      
filename: md_fixed.pckl.gzip # force to read reference pickled dataframe from given file
      aug_factor: 1e-4 # common prefactor for weights of augmented structures
      reference_energy: auto
      #################################################################
      Fit specification section
      #################################################################
      
fit:
      
loss: { kappa: 0.3, L1_coeffs: 1e-8, L2_coeffs: 1e-8}
      if kappa: auto, then it will be determined from the variation of energy per atom and forces norms in train set
      weighting: { type: EnergyBasedWeightingPolicy, DElow: 1.0, DEup: 10.0, DFup: 50.0, DE: 1.0, DF: 1.0, wlow: 0.75, energy: convex_hull, reftype: all,seed: 42}
      optimizer: BFGS # or L-BFGS-B
      maximum number of minimize iterations
      maxiter: 2000
      additional options for scipy.minimize
      options: {maxcor: 100}
      Automatically find the smallest interatomic distance in dataset and set inner cutoff for ZBL to it
      repulsion: auto
      ladder_step: 100
      ladder_type: power_order
      Early stopping
      min_relative_train_loss_per_iter: 5e-5
      min_relative_test_loss_per_iter: 1e-5
      early_stopping_patience: 200
      #################################################################
      Backend specification section
      #################################################################
      
backend:
      
evaluator: tensorpot
      
batch_size: 100
      
display_step: 50
      Metadata
      Metadata
      Assignees
      No one assigned
        Labels
        No labels
        No labels
        Type
        No type
        Projects
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          Milestone
          No milestone
          Relationships
          None yet
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          No branches or pull requests
          Issue actions
          
, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

          Skip to content
          unhashable type: 'list' #84
          Open
          Open
          unhashable type: 'list'#84
          Description
          @Snehal-V2
          Snehal-V2
          opened on Dec 30, 2024
          HI,im trying to run input.yaml file through pacemaker but im getting this error. I dont know how to use it.
          
cutoff: 7.0 # cutoff for neighbour list construction
          
seed: 42 # random seed
          #################################################################
          Metadata section
          #################################################################
          
metadata:
          
origin: "Automatically generated input"
          #################################################################
          Potential definition section
          #################################################################
          
potential:
          
deltaSplineBins: 0.001
          
elements: ['S', 'S', 'W', 'W']
          embeddings:
          
ALL: {
          
npot: 'FinnisSinclairShiftedScaled',
          
fs_parameters: [ 1, 1, 1, 0.5 ],
          
ndensity: 2,
          
}
          bonds:
          
ALL: {
          
radbase: SBessel,
          
radparameters: [ 5.25 ],
          
rcut: 7.0,
          
dcut: 0.01,
          
NameOfCutoffFunction: cos,
          
}
          functions:
          
number_of_functions_per_element: 700
          
UNARY: { nradmax_by_orders: [ 15, 6, 4, 3, 2, 2 ], lmax_by_orders: [ 0 , 3, 3, 2, 2, 1 ]}
          
BINARY: { nradmax_by_orders: [ 15, 6, 3, 2, 2, 1 ], lmax_by_orders: [ 0 , 3, 2, 1, 1, 0 ]}
          
TERNARY: { nradmax_by_orders: [ 15, 3, 3, 2, 1 ], lmax_by_orders: [ 0 , 2, 2, 1, 1 ], }
          
ALL: { nradmax_by_orders: [ 15, 3, 2, 1, 1 ], lmax_by_orders: [ 0 , 2, 2, 1, 1 ] }
          #################################################################
          Dataset specification section
          #################################################################
          
data:
          
filename: md_fixed.pckl.gzip # force to read reference pickled dataframe from given file
          aug_factor: 1e-4 # common prefactor for weights of augmented structures
          reference_energy: auto
          #################################################################
          Fit specification section
          #################################################################
          
fit:
          
loss: { kappa: 0.3, L1_coeffs: 1e-8, L2_coeffs: 1e-8}
          if kappa: auto, then it will be determined from the variation of energy per atom and forces norms in train set
          weighting: { type: EnergyBasedWeightingPolicy, DElow: 1.0, DEup: 10.0, DFup: 50.0, DE: 1.0, DF: 1.0, wlow: 0.75, energy: convex_hull, reftype: all,seed: 42}
          optimizer: BFGS # or L-BFGS-B
          maximum number of minimize iterations
          maxiter: 2000
          additional options for scipy.minimize
          options: {maxcor: 100}
          Automatically find the smallest interatomic distance in dataset and set inner cutoff for ZBL to it
          repulsion: auto
          ladder_step: 100
          ladder_type: power_order
          Early stopping
          min_relative_train_loss_per_iter: 5e-5
          min_relative_test_loss_per_iter: 1e-5
          early_stopping_patience: 200
          #################################################################
          Backend specification section
          #################################################################
          
backend:
          
evaluator: tensorpot
          
batch_size: 100
          
display_step: 50
          Metadata
          Metadata
          Assignees
          No one assigned
            Labels
            No labels
            No labels
            Type
            No type
            Projects
            No projects
              Milestone
              No milestone
              Relationships
              None yet
              Development
              No branches or pull requests
              Issue actions
              
, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

              Skip to content
              unhashable type: 'list' #84
              Open
              Open
              unhashable type: 'list'#84
              Description
              @Snehal-V2
              Snehal-V2
              opened on Dec 30, 2024
              HI,im trying to run input.yaml file through pacemaker but im getting this error. I dont know how to use it.
              
cutoff: 7.0 # cutoff for neighbour list construction
              
seed: 42 # random seed
              #################################################################
              Metadata section
              #################################################################
              
metadata:
              
origin: "Automatically generated input"
              #################################################################
              Potential definition section
              #################################################################
              
potential:
              
deltaSplineBins: 0.001
              
elements: ['S', 'S', 'W', 'W']
              embeddings:
              
ALL: {
              
npot: 'FinnisSinclairShiftedScaled',
              
fs_parameters: [ 1, 1, 1, 0.5 ],
              
ndensity: 2,
              
}
              bonds:
              
ALL: {
              
radbase: SBessel,
              
radparameters: [ 5.25 ],
              
rcut: 7.0,
              
dcut: 0.01,
              
NameOfCutoffFunction: cos,
              
}
              functions:
              
number_of_functions_per_element: 700
              
UNARY: { nradmax_by_orders: [ 15, 6, 4, 3, 2, 2 ], lmax_by_orders: [ 0 , 3, 3, 2, 2, 1 ]}
              
BINARY: { nradmax_by_orders: [ 15, 6, 3, 2, 2, 1 ], lmax_by_orders: [ 0 , 3, 2, 1, 1, 0 ]}
              
TERNARY: { nradmax_by_orders: [ 15, 3, 3, 2, 1 ], lmax_by_orders: [ 0 , 2, 2, 1, 1 ], }
              
ALL: { nradmax_by_orders: [ 15, 3, 2, 1, 1 ], lmax_by_orders: [ 0 , 2, 2, 1, 1 ] }
              #################################################################
              Dataset specification section
              #################################################################
              
data:
              
filename: md_fixed.pckl.gzip # force to read reference pickled dataframe from given file
              aug_factor: 1e-4 # common prefactor for weights of augmented structures
              reference_energy: auto
              #################################################################
              Fit specification section
              #################################################################
              
fit:
              
loss: { kappa: 0.3, L1_coeffs: 1e-8, L2_coeffs: 1e-8}
              if kappa: auto, then it will be determined from the variation of energy per atom and forces norms in train set
              weighting: { type: EnergyBasedWeightingPolicy, DElow: 1.0, DEup: 10.0, DFup: 50.0, DE: 1.0, DF: 1.0, wlow: 0.75, energy: convex_hull, reftype: all,seed: 42}
              optimizer: BFGS # or L-BFGS-B
              maximum number of minimize iterations
              maxiter: 2000
              additional options for scipy.minimize
              options: {maxcor: 100}
              Automatically find the smallest interatomic distance in dataset and set inner cutoff for ZBL to it
              repulsion: auto
              ladder_step: 100
              ladder_type: power_order
              Early stopping
              min_relative_train_loss_per_iter: 5e-5
              min_relative_test_loss_per_iter: 1e-5
              early_stopping_patience: 200
              #################################################################
              Backend specification section
              #################################################################
              
backend:
              
evaluator: tensorpot
              
batch_size: 100
              
display_step: 50
              Metadata
              Metadata
              Assignees
              No one assigned
                Labels
                No labels
                No labels
                Type
                No type
                Projects
                No projects
                  Milestone
                  No milestone
                  Relationships
                  None yet
                  Development
                  No branches or pull requests
                  Issue actions
                  
, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

                  Skip to content
                  unhashable type: 'list' #84
                  Open
                  Open
                  unhashable type: 'list'#84
                  Description
                  @Snehal-V2
                  Snehal-V2
                  opened on Dec 30, 2024
                  HI,im trying to run input.yaml file through pacemaker but im getting this error. I dont know how to use it.
                  
cutoff: 7.0 # cutoff for neighbour list construction
                  
seed: 42 # random seed
                  #################################################################
                  Metadata section
                  #################################################################
                  
metadata:
                  
origin: "Automatically generated input"
                  #################################################################
                  Potential definition section
                  #################################################################
                  
potential:
                  
deltaSplineBins: 0.001
                  
elements: ['S', 'S', 'W', 'W']
                  embeddings:
                  
ALL: {
                  
npot: 'FinnisSinclairShiftedScaled',
                  
fs_parameters: [ 1, 1, 1, 0.5 ],
                  
ndensity: 2,
                  
}
                  bonds:
                  
ALL: {
                  
radbase: SBessel,
                  
radparameters: [ 5.25 ],
                  
rcut: 7.0,
                  
dcut: 0.01,
                  
NameOfCutoffFunction: cos,
                  
}
                  functions:
                  
number_of_functions_per_element: 700
                  
UNARY: { nradmax_by_orders: [ 15, 6, 4, 3, 2, 2 ], lmax_by_orders: [ 0 , 3, 3, 2, 2, 1 ]}
                  
BINARY: { nradmax_by_orders: [ 15, 6, 3, 2, 2, 1 ], lmax_by_orders: [ 0 , 3, 2, 1, 1, 0 ]}
                  
TERNARY: { nradmax_by_orders: [ 15, 3, 3, 2, 1 ], lmax_by_orders: [ 0 , 2, 2, 1, 1 ], }
                  
ALL: { nradmax_by_orders: [ 15, 3, 2, 1, 1 ], lmax_by_orders: [ 0 , 2, 2, 1, 1 ] }
                  #################################################################
                  Dataset specification section
                  #################################################################
                  
data:
                  
filename: md_fixed.pckl.gzip # force to read reference pickled dataframe from given file
                  aug_factor: 1e-4 # common prefactor for weights of augmented structures
                  reference_energy: auto
                  #################################################################
                  Fit specification section
                  #################################################################
                  
fit:
                  
loss: { kappa: 0.3, L1_coeffs: 1e-8, L2_coeffs: 1e-8}
                  if kappa: auto, then it will be determined from the variation of energy per atom and forces norms in train set
                  weighting: { type: EnergyBasedWeightingPolicy, DElow: 1.0, DEup: 10.0, DFup: 50.0, DE: 1.0, DF: 1.0, wlow: 0.75, energy: convex_hull, reftype: all,seed: 42}
                  optimizer: BFGS # or L-BFGS-B
                  maximum number of minimize iterations
                  maxiter: 2000
                  additional options for scipy.minimize
                  options: {maxcor: 100}
                  Automatically find the smallest interatomic distance in dataset and set inner cutoff for ZBL to it
                  repulsion: auto
                  ladder_step: 100
                  ladder_type: power_order
                  Early stopping
                  min_relative_train_loss_per_iter: 5e-5
                  min_relative_test_loss_per_iter: 1e-5
                  early_stopping_patience: 200
                  #################################################################
                  Backend specification section
                  #################################################################
                  
backend:
                  
evaluator: tensorpot
                  
batch_size: 100
                  
display_step: 50
                  Metadata
                  Metadata
                  Assignees
                  No one assigned
                    Labels
                    No labels
                    No labels
                    Type
                    No type
                    Projects
                    No projects
                      Milestone
                      No milestone
                      Relationships
                      None yet
                      Development
                      No branches or pull requests
                      Issue actions
                      
, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

                      Skip to content
                      unhashable type: 'list' #84
                      Open
                      Open
                      unhashable type: 'list'#84
                      Description
                      @Snehal-V2
                      Snehal-V2
                      opened on Dec 30, 2024
                      HI,im trying to run input.yaml file through pacemaker but im getting this error. I dont know how to use it.
                      
cutoff: 7.0 # cutoff for neighbour list construction
                      
seed: 42 # random seed
                      #################################################################
                      Metadata section
                      #################################################################
                      
metadata:
                      
origin: "Automatically generated input"
                      #################################################################
                      Potential definition section
                      #################################################################
                      
potential:
                      
deltaSplineBins: 0.001
                      
elements: ['S', 'S', 'W', 'W']
                      embeddings:
                      
ALL: {
                      
npot: 'FinnisSinclairShiftedScaled',
                      
fs_parameters: [ 1, 1, 1, 0.5 ],
                      
ndensity: 2,
                      
}
                      bonds:
                      
ALL: {
                      
radbase: SBessel,
                      
radparameters: [ 5.25 ],
                      
rcut: 7.0,
                      
dcut: 0.01,
                      
NameOfCutoffFunction: cos,
                      
}
                      functions:
                      
number_of_functions_per_element: 700
                      
UNARY: { nradmax_by_orders: [ 15, 6, 4, 3, 2, 2 ], lmax_by_orders: [ 0 , 3, 3, 2, 2, 1 ]}
                      
BINARY: { nradmax_by_orders: [ 15, 6, 3, 2, 2, 1 ], lmax_by_orders: [ 0 , 3, 2, 1, 1, 0 ]}
                      
TERNARY: { nradmax_by_orders: [ 15, 3, 3, 2, 1 ], lmax_by_orders: [ 0 , 2, 2, 1, 1 ], }
                      
ALL: { nradmax_by_orders: [ 15, 3, 2, 1, 1 ], lmax_by_orders: [ 0 , 2, 2, 1, 1 ] }
                      #################################################################
                      Dataset specification section
                      #################################################################
                      
data:
                      
filename: md_fixed.pckl.gzip # force to read reference pickled dataframe from given file
                      aug_factor: 1e-4 # common prefactor for weights of augmented structures
                      reference_energy: auto
                      #################################################################
                      Fit specification section
                      #################################################################
                      
fit:
                      
loss: { kappa: 0.3, L1_coeffs: 1e-8, L2_coeffs: 1e-8}
                      if kappa: auto, then it will be determined from the variation of energy per atom and forces norms in train set
                      weighting: { type: EnergyBasedWeightingPolicy, DElow: 1.0, DEup: 10.0, DFup: 50.0, DE: 1.0, DF: 1.0, wlow: 0.75, energy: convex_hull, reftype: all,seed: 42}
                      optimizer: BFGS # or L-BFGS-B
                      maximum number of minimize iterations
                      maxiter: 2000
                      additional options for scipy.minimize
                      options: {maxcor: 100}
                      Automatically find the smallest interatomic distance in dataset and set inner cutoff for ZBL to it
                      repulsion: auto
                      ladder_step: 100
                      ladder_type: power_order
                      Early stopping
                      min_relative_train_loss_per_iter: 5e-5
                      min_relative_test_loss_per_iter: 1e-5
                      early_stopping_patience: 200
                      #################################################################
                      Backend specification section
                      #################################################################
                      
backend:
                      
evaluator: tensorpot
                      
batch_size: 100
                      
display_step: 50
                      Metadata
                      Metadata
                      Assignees
                      No one assigned
                        Labels
                        No labels
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                          None yet
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                          No branches or pull requests
                          Issue actions
                          
, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

                          Skip to content
                          unhashable type: 'list' #84
                          Open
                          Open
                          unhashable type: 'list'#84
                          Description
                          @Snehal-V2
                          Snehal-V2
                          opened on Dec 30, 2024
                          HI,im trying to run input.yaml file through pacemaker but im getting this error. I dont know how to use it.
                          
cutoff: 7.0 # cutoff for neighbour list construction
                          
seed: 42 # random seed
                          #################################################################
                          Metadata section
                          #################################################################
                          
metadata:
                          
origin: "Automatically generated input"
                          #################################################################
                          Potential definition section
                          #################################################################
                          
potential:
                          
deltaSplineBins: 0.001
                          
elements: ['S', 'S', 'W', 'W']
                          embeddings:
                          
ALL: {
                          
npot: 'FinnisSinclairShiftedScaled',
                          
fs_parameters: [ 1, 1, 1, 0.5 ],
                          
ndensity: 2,
                          
}
                          bonds:
                          
ALL: {
                          
radbase: SBessel,
                          
radparameters: [ 5.25 ],
                          
rcut: 7.0,
                          
dcut: 0.01,
                          
NameOfCutoffFunction: cos,
                          
}
                          functions:
                          
number_of_functions_per_element: 700
                          
UNARY: { nradmax_by_orders: [ 15, 6, 4, 3, 2, 2 ], lmax_by_orders: [ 0 , 3, 3, 2, 2, 1 ]}
                          
BINARY: { nradmax_by_orders: [ 15, 6, 3, 2, 2, 1 ], lmax_by_orders: [ 0 , 3, 2, 1, 1, 0 ]}
                          
TERNARY: { nradmax_by_orders: [ 15, 3, 3, 2, 1 ], lmax_by_orders: [ 0 , 2, 2, 1, 1 ], }
                          
ALL: { nradmax_by_orders: [ 15, 3, 2, 1, 1 ], lmax_by_orders: [ 0 , 2, 2, 1, 1 ] }
                          #################################################################
                          Dataset specification section
                          #################################################################
                          
data:
                          
filename: md_fixed.pckl.gzip # force to read reference pickled dataframe from given file
                          aug_factor: 1e-4 # common prefactor for weights of augmented structures
                          reference_energy: auto
                          #################################################################
                          Fit specification section
                          #################################################################
                          
fit:
                          
loss: { kappa: 0.3, L1_coeffs: 1e-8, L2_coeffs: 1e-8}
                          if kappa: auto, then it will be determined from the variation of energy per atom and forces norms in train set
                          weighting: { type: EnergyBasedWeightingPolicy, DElow: 1.0, DEup: 10.0, DFup: 50.0, DE: 1.0, DF: 1.0, wlow: 0.75, energy: convex_hull, reftype: all,seed: 42}
                          optimizer: BFGS # or L-BFGS-B
                          maximum number of minimize iterations
                          maxiter: 2000
                          additional options for scipy.minimize
                          options: {maxcor: 100}
                          Automatically find the smallest interatomic distance in dataset and set inner cutoff for ZBL to it
                          repulsion: auto
                          ladder_step: 100
                          ladder_type: power_order
                          Early stopping
                          min_relative_train_loss_per_iter: 5e-5
                          min_relative_test_loss_per_iter: 1e-5
                          early_stopping_patience: 200
                          #################################################################
                          Backend specification section
                          #################################################################
                          
backend:
                          
evaluator: tensorpot
                          
batch_size: 100
                          
display_step: 50
                          Metadata
                          Metadata
                          Assignees
                          No one assigned
                            Labels
                            No labels
                            No labels
                            Type
                            No type
                            Projects
                            No projects
                              Milestone
                              No milestone
                              Relationships
                              None yet
                              Development
                              No branches or pull requests
                              Issue actions
                              
, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

                              Skip to content
                              unhashable type: 'list' #84
                              Open
                              Open
                              unhashable type: 'list'#84
                              Description
                              @Snehal-V2
                              Snehal-V2
                              opened on Dec 30, 2024
                              HI,im trying to run input.yaml file through pacemaker but im getting this error. I dont know how to use it.
                              
cutoff: 7.0 # cutoff for neighbour list construction
                              
seed: 42 # random seed
                              #################################################################
                              Metadata section
                              #################################################################
                              
metadata:
                              
origin: "Automatically generated input"
                              #################################################################
                              Potential definition section
                              #################################################################
                              
potential:
                              
deltaSplineBins: 0.001
                              
elements: ['S', 'S', 'W', 'W']
                              embeddings:
                              
ALL: {
                              
npot: 'FinnisSinclairShiftedScaled',
                              
fs_parameters: [ 1, 1, 1, 0.5 ],
                              
ndensity: 2,
                              
}
                              bonds:
                              
ALL: {
                              
radbase: SBessel,
                              
radparameters: [ 5.25 ],
                              
rcut: 7.0,
                              
dcut: 0.01,
                              
NameOfCutoffFunction: cos,
                              
}
                              functions:
                              
number_of_functions_per_element: 700
                              
UNARY: { nradmax_by_orders: [ 15, 6, 4, 3, 2, 2 ], lmax_by_orders: [ 0 , 3, 3, 2, 2, 1 ]}
                              
BINARY: { nradmax_by_orders: [ 15, 6, 3, 2, 2, 1 ], lmax_by_orders: [ 0 , 3, 2, 1, 1, 0 ]}
                              
TERNARY: { nradmax_by_orders: [ 15, 3, 3, 2, 1 ], lmax_by_orders: [ 0 , 2, 2, 1, 1 ], }
                              
ALL: { nradmax_by_orders: [ 15, 3, 2, 1, 1 ], lmax_by_orders: [ 0 , 2, 2, 1, 1 ] }
                              #################################################################
                              Dataset specification section
                              #################################################################
                              
data:
                              
filename: md_fixed.pckl.gzip # force to read reference pickled dataframe from given file
                              aug_factor: 1e-4 # common prefactor for weights of augmented structures
                              reference_energy: auto
                              #################################################################
                              Fit specification section
                              #################################################################
                              
fit:
                              
loss: { kappa: 0.3, L1_coeffs: 1e-8, L2_coeffs: 1e-8}
                              if kappa: auto, then it will be determined from the variation of energy per atom and forces norms in train set
                              weighting: { type: EnergyBasedWeightingPolicy, DElow: 1.0, DEup: 10.0, DFup: 50.0, DE: 1.0, DF: 1.0, wlow: 0.75, energy: convex_hull, reftype: all,seed: 42}
                              optimizer: BFGS # or L-BFGS-B
                              maximum number of minimize iterations
                              maxiter: 2000
                              additional options for scipy.minimize
                              options: {maxcor: 100}
                              Automatically find the smallest interatomic distance in dataset and set inner cutoff for ZBL to it
                              repulsion: auto
                              ladder_step: 100
                              ladder_type: power_order
                              Early stopping
                              min_relative_train_loss_per_iter: 5e-5
                              min_relative_test_loss_per_iter: 1e-5
                              early_stopping_patience: 200
                              #################################################################
                              Backend specification section
                              #################################################################
                              
backend:
                              
evaluator: tensorpot
                              
batch_size: 100
                              
display_step: 50
                              Metadata
                              Metadata
                              Assignees
                              No one assigned
                                Labels
                                No labels
                                No labels
                                Type
                                No type
                                Projects
                                No projects
                                  Milestone
                                  No milestone
                                  Relationships
                                  None yet
                                  Development
                                  No branches or pull requests
                                  Issue actions