python_code stringlengths 0 679k | repo_name stringlengths 9 41 | file_path stringlengths 6 149 |
|---|---|---|
import json
import ipyvuetify as v
from .appLoader import AppLoader
from .common import load_template
# update the CSS a bit
# get_ipython().run_cell_magic(
# "HTML",
# "",
# "<style>\n.jp-Cell {\n margin:unset;\n padding: unset;\n}\n.jp-Cell:not(.jp-mod-noOutputs) .jp-Cell-outputWrapper{\n mar... | modulus-toolchain-master | mpc/nvapp/app.py |
import ipyvuetify as v
import traitlets as tr
from .common import load_template, reload_module
import ipywidgets as ipw
import time
class AppLoader(v.VuetifyTemplate):
template = tr.Unicode(load_template("vue-templates/app-loader.vue")).tag(sync=True)
apps = tr.List(["widget1", "widget2"]).tag(sync=True)
... | modulus-toolchain-master | mpc/nvapp/appLoader.py |
from .app import new
| modulus-toolchain-master | mpc/demoYAMLv1/__init__.py |
import os, time
import ipywidgets as ipw
import ipyvuetify as v
import time
import traitlets as tr
import os
def load_template(filename):
with open(os.path.join(os.path.dirname(__file__), filename)) as f:
return f.read()
var2name = {"lr": "Learning Rate"}
var2hint = {
"eps": "Numerical threshold b... | modulus-toolchain-master | mpc/demoYAMLv1/app.py |
from .app import new
| modulus-toolchain-master | mpc/mpc/__init__.py |
import os, time
import ipywidgets as ipw
import ipyvuetify as v
import time
import traitlets as tr
import os
import sys
sys.path.append(os.environ["MPC_PATH"] + "../mtc")
print(sys.path)
from mtc.config_utils import customize_schema, config2dictV2
def load_template(filename):
with open(os.path.join(os.path.dir... | modulus-toolchain-master | mpc/mpc/app.py |
from .app import new
| modulus-toolchain-master | mpc/demoYAMLv2/__init__.py |
import os, time
import ipywidgets as ipw
import ipyvuetify as v
import time
import traitlets as tr
import os
def load_template(filename):
with open(os.path.join(os.path.dirname(__file__), filename)) as f:
return f.read()
var2name = {"lr": "Learning Rate"}
var2hint = {
"eps": "Numerical threshold b... | modulus-toolchain-master | mpc/demoYAMLv2/app.py |
from cfg import *
import numpy as np
from sympy import exp, sin, cos, DiracDelta
##########################################################
####################### Neural networks ##################
##########################################################
# Create NN to predict pressure (x,y,t) -> p
[x, y, t], [pres... | modulus-toolchain-master | examples/PINNs/04-WaveEquationPINNs/we-2d-fwd/solutions/we-fwd-2d-cv-snapshots-problem.py |
from cfg import *
import numpy as np
from sympy import exp, sin
# Create NN to predict pressure (x,t) -> p
[x, t], [u] = p.add_neural_network(name="pressure", inputs=["x", "t"], outputs=["u"])
# Create NN to predict velocity (x,t) -> vel
[x], [vel] = p.add_neural_network(name="velocity", inputs=["x"], outputs=["vel"]... | modulus-toolchain-master | examples/PINNs/04-WaveEquationPINNs/we-1d-inv/solutions/we-inv-1d-vel-noderiv-problem.py |
from cfg import *
import numpy as np
from sympy import exp, sin
################ Neural Network defintion ################
# Create NN to predict pressure (x,t) -> p
[x, t], [u] = p.add_neural_network(name="pressure", inputs=["x", "t"], outputs=["u"])
# Create NN to predict velocity (x) -> vel
[x], [vel] = p.add_neur... | modulus-toolchain-master | examples/PINNs/04-WaveEquationPINNs/we-1d-inv/solutions/we-inv-1d-vel-2layers-deriv-problem.py |
from cfg import *
import numpy as np
from sympy import exp, sin
################ Neural Network defintion ################
# Create NN to predict pressure (x,t) -> p
[x, t], [u] = p.add_neural_network(name="pressure", inputs=["x", "t"], outputs=["u"])
# Create NN to predict velocity (x) -> vel
[x], [vel] = p.add_neu... | modulus-toolchain-master | examples/PINNs/04-WaveEquationPINNs/we-1d-inv/solutions/we-inv-1d-vel-3layers-deriv-problem.py |
from cfg import *
import numpy as np
from sympy import exp, sin
################ Neural Network defintion ################
# Create NN to predict pressure (x,t) -> p
[x, t], [u] = p.add_neural_network(name="pressure", inputs=["x", "t"], outputs=["u"])
# Create NN to predict velocity (x) -> vel
[x], [vel] = p.add_neur... | modulus-toolchain-master | examples/PINNs/04-WaveEquationPINNs/we-1d-inv/solutions/we-inv-1d-vel-4layers-deriv-problem.py |
from cfg import *
import numpy as np
from sympy import exp, sin
# Create NN to predict pressure (x,t) -> p
[x, t], [u] = p.add_neural_network(name="pressure", inputs=["x", "t"], outputs=["u"])
# Create NN to predict velocity (x,t) -> vel
[x], [vel] = p.add_neural_network(name="velocity", inputs=["x"], outputs=["vel"]... | modulus-toolchain-master | examples/PINNs/04-WaveEquationPINNs/we-1d-inv/solutions/we-inv-1d-vel-deriv-problem.py |
from cfg import *
import numpy as np
from sympy import exp, sin
# Create NN to predict pressure (x,t) -> p
[x, t], [u] = p.add_neural_network(name="pressure", inputs=["x", "t"], outputs=["u"])
# Create NN to predict velocity (x,t) -> vel
[x], [vel] = p.add_neural_network(name="velocity", inputs=["x"], outputs=["vel"]... | modulus-toolchain-master | examples/PINNs/04-WaveEquationPINNs/we-1d-inv/solutions/we-inv-1d-vel-problem.py |
from cfg import *
import numpy as np
from sympy import exp, sin
# Vel is also an input
[x, t, vel], [u] = p.add_neural_network(name="wave1d", inputs=["x", "t", "vel"], outputs=["u"])
# Geometry + domains
L = float(np.pi)
geo = p.Line1D("geom", 0, L)
interior = p.add_interior_subdomain("interior", geom=geo, params={... | modulus-toolchain-master | examples/PINNs/04-WaveEquationPINNs/we-1d-fwd/solutions/we-fwd-1d-vel-problem.py |
from cfg import *
import numpy as np
from sympy import exp, sin
# Create NN that maps (position,time) -> pressure
[x, t], [u] = p.add_neural_network(name="wave1d", inputs=["x", "t"], outputs=["u"])
# Geometry
L = float(np.pi)
geo = p.Line1D("geom", 0, L)
# Domains
# Do not forget to add the time parametrization
in... | modulus-toolchain-master | examples/PINNs/04-WaveEquationPINNs/we-1d-fwd/solutions/we-fwd-1d-cv-problem.py |
from cfg import *
import numpy as np
from sympy import exp, sin
# Neural net (position,time) -> pressure
[x, t], [u] = p.add_neural_network(name="wave1d", inputs=["x", "t"], outputs=["u"])
# Geometry
L = float(np.pi)
geo = p.Line1D("geom", 0, L)
# Domains + time parametrization
interior = p.add_interior_subdomain("... | modulus-toolchain-master | examples/PINNs/04-WaveEquationPINNs/we-1d-fwd/solutions/we-fwd-1d-ncv-problem.py |
from cfg import *
import numpy as np
from sympy import exp, sin
# Vel is also an input
[x, t, k], [u] = p.add_neural_network(name="wave1d", inputs=["x", "t", "k"], outputs=["u"])
# Geometry + domains
L = float(np.pi)
geo = p.Line1D("geom", 0, L)
interior = p.add_interior_subdomain("interior", geom=geo, params={t:(0... | modulus-toolchain-master | examples/PINNs/04-WaveEquationPINNs/we-1d-fwd/solutions/we-fwd-1d-vel-k-problem.py |
from cfg import *
[x, y, rot], [u, pp, v] = p.add_neural_network(
name="NN", inputs=["x", "y", "rot"], outputs=["u", "p", "v"]
)
# geometry
import numpy as np
params = {rot: (0, -np.pi / 6)}
# params = {rot: float(0.0)}
channel_length = 15.0 / 2
channel_height = 10.0 / 2
a = 0.3
channel_rect = p.Rectangle(
... | modulus-toolchain-master | examples/PINNs/03-Airfoil/airfoil-custom-geom-problem.py |
import numpy as np
from modulus.geometry.primitives_2d import Channel2D, Rectangle
import matplotlib.pyplot as plt
import warp as wp
import numpy as np
import os
wp.init()
# Naca implementation modified from https://stackoverflow.com/questions/31815041/plotting-a-naca-4-series-airfoil
# https://en.wikipedia.org/w... | modulus-toolchain-master | examples/PINNs/03-Airfoil/CustomAirfoilGeom.py |
from cfg import *
[x, y, rot], [u, pp, v] = p.add_neural_network(
name="NN", inputs=["x", "y", "rot"], outputs=["u", "p", "v"]
)
# geometry
import numpy as np
lines = [[0, 0], [1, 0], [1, 1]]
from sympy import Number, Symbol, Heaviside, atan, sin, cos, sqrt
# Naca implementation modified from https://stackove... | modulus-toolchain-master | examples/PINNs/03-Airfoil/airfoil_rot_only_problem.py |
from cfg import *
[x, y], [T] = p.add_neural_network(name="NN_Tsolid", inputs=["x", "y"], outputs=[ "Tsolid"])
geo_solid = p.Rectangle("rect", (0,0), (1,1))
interior_solid = p.add_interior_subdomain("interior_solid", geom=geo_solid)
bdry_solid = p.add_boundary_subdomain("bdry_solid", geom=geo_solid, criteria=y>0)
bdr... | modulus-toolchain-master | examples/PINNs/01-PracticeProblems/solutions/s3p1a.py |
from cfg import *
import sympy as sp
# HEAT
[x, y], [T] = p.add_neural_network(name="NN_Tsolid", inputs=["x", "y"], outputs=[ "Tsolid"])
geo_solid = p.Rectangle("rect", (0,0), (1,1))
interior_solid = p.add_interior_subdomain("interior_solid", geom=geo_solid)
bdry_solid = p.add_boundary_subdomain("bdry_solid", geom=g... | modulus-toolchain-master | examples/PINNs/01-PracticeProblems/solutions/s3p2a.py |
from cfg import *
import sympy as sp
# HEAT
[x, y], [T] = p.add_neural_network(name="NN_Tsolid", inputs=["x", "y"], outputs=[ "Tsolid"])
geo_solid = p.Rectangle("rect", (0,0), (1,1))
interior_solid = p.add_interior_subdomain("interior_solid", geom=geo_solid)
bdry_solid = p.add_boundary_subdomain("bdry_solid", geom=g... | modulus-toolchain-master | examples/PINNs/01-PracticeProblems/solutions/s3p2d.py |
from cfg import *
[x], [ua, ub] = p.add_neural_network(name="NN", inputs=["x"], outputs=["ua", "ub"])
geom = p.Line1D("geomA", -1,0)
interior = p.add_interior_subdomain("interiorA", geom=geom)
middle = p.add_boundary_subdomain("middle", geom=geom, criteria=Eq(x,0))
bdry = p.add_boundary_subdomain("bdryA", geom=geom... | modulus-toolchain-master | examples/PINNs/01-PracticeProblems/solutions/p2c.py |
from cfg import *
[x, y], [u] = p.add_neural_network(name="NN", inputs=["x", "y"], outputs=["u"])
w,h = 2,1
r1 = p.Rectangle("r1", (0,0), (w,h))
ch1 = p.Channel2D("ch1", (0,0), (w,h))
inlet = p.add_boundary_subdomain("inlet", geom=r1, criteria=Eq(x,0))
outlet = p.add_boundary_subdomain("outlet", geom=r1, criteria=Eq... | modulus-toolchain-master | examples/PINNs/01-PracticeProblems/solutions/s2p1a.py |
from cfg import *
[x, y], [u, v, pp] = p.add_neural_network(name="NN", inputs=["x", "y"], outputs=["u", "v", "p"])
w,h = 2,1
r1 = p.Rectangle("r1", (0,0), (w,h))
ch1 = p.Channel2D("ch1", (0,0), (w,h))
subr = p.Rectangle("subr1", (w/2-.1,0), (w/2+.1,h*.8))
ch1 = p.GeometryDifference("gd", ch1, subr)
inlet = p.add_bo... | modulus-toolchain-master | examples/PINNs/01-PracticeProblems/solutions/s2p2e.py |
from cfg import *
[x], [ua, ub] = p.add_neural_network(name="NN", inputs=["x"], outputs=["ua", "ub"])
geom = p.Line1D("geomA", -1,0)
interior = p.add_interior_subdomain("interiorA", geom=geom)
middle = p.add_boundary_subdomain("middle", geom=geom, criteria=Eq(x,0))
bdry = p.add_boundary_subdomain("bdryA", geom=geom... | modulus-toolchain-master | examples/PINNs/01-PracticeProblems/solutions/p1c.py |
from cfg import *
[x], [ua, ub] = p.add_neural_network(name="NN", inputs=["x"], outputs=["ua", "ub"])
DA = 1
DB = 1/100
geom = p.Line1D("geomA", -1,0)
interior = p.add_interior_subdomain("interiorA", geom=geom)
middle = p.add_boundary_subdomain("middle", geom=geom, criteria=Eq(x,0))
bdry = p.add_boundary_subdomain... | modulus-toolchain-master | examples/PINNs/01-PracticeProblems/solutions/p2b.py |
from cfg import *
[x, y], [u, v, pp] = p.add_neural_network(name="NN", inputs=["x", "y"], outputs=["u", "v", "p"])
w,h = 2,1
r1 = p.Rectangle("r1", (0,0), (w,h))
ch1 = p.Channel2D("ch1", (0,0), (w,h))
inlet = p.add_boundary_subdomain("inlet", geom=r1, criteria=Eq(x,0))
outlet = p.add_boundary_subdomain("outlet", geo... | modulus-toolchain-master | examples/PINNs/01-PracticeProblems/solutions/s2p1c.py |
from cfg import *
[x], [ua, ub] = p.add_neural_network(name="NN", inputs=["x"], outputs=["ua", "ub"])
geom = p.Line1D("geomA", -1,0)
interior = p.add_interior_subdomain("interiorA", geom=geom)
bdry = p.add_boundary_subdomain("bdryA", geom=geom)
diff_eq = Eq(ua.diff(x,2) + 1, 0)
p.add_constraint("diffusionA", enforce(... | modulus-toolchain-master | examples/PINNs/01-PracticeProblems/solutions/p1a.py |
from cfg import *
[x, v1,v2], [va, vb] = p.add_neural_network(name="NN", inputs=["x", 'v1', 'v2'], outputs=["va", "vb"])
ua = p.add_submodel("ua", va*(x+1)+v1)
ub = p.add_submodel("ub", vb*(x-1)+v2)
params={v1:(-1,1), v2:(-1,1)}
DA = 1
DB = 1/100
geom = p.Line1D("geomA", -1,0)
interior = p.add_interior_subdomain("... | modulus-toolchain-master | examples/PINNs/01-PracticeProblems/solutions/p3a.py |
from cfg import *
[x, y, oh], [u, v, pp] = p.add_neural_network(name="NN", inputs=["x", "y", "oh"], outputs=["u", "v", "p"])
w,h = 2,1
r1 = p.Rectangle("r1", (0,0), (w,h))
ch1 = p.Channel2D("ch1", (0,0), (w,h))
params = {oh: (0,0.95)}
# subr = p.Rectangle("subr1", (w/2-.1,0), (w/2+.1,h*.8))
subr = p.Rectangle("subr... | modulus-toolchain-master | examples/PINNs/01-PracticeProblems/solutions/s2p3.py |
from cfg import *
[x, y], [u, v, pp] = p.add_neural_network(name="NN", inputs=["x", "y"], outputs=["u", "v", "p"])
w,h = 2,1
r1 = p.Rectangle("r1", (0,0), (w,h))
ch1 = p.Channel2D("ch1", (0,0), (w,h))
subr = p.Rectangle("subr1", (w/2-.1,0), (w/2+.1,h*.8))
ch1 = p.GeometryDifference("gd", ch1, subr)
inlet = p.add_bo... | modulus-toolchain-master | examples/PINNs/01-PracticeProblems/solutions/s2p2c.py |
from cfg import *
import sympy as sp
# HEAT
[x, y], [T] = p.add_neural_network(name="NN_Tsolid", inputs=["x", "y"], outputs=[ "Tsolid"])
geo_solid = p.Rectangle("rect", (0,0), (1,1))
interior_solid = p.add_interior_subdomain("interior_solid", geom=geo_solid)
bdry_solid = p.add_boundary_subdomain("bdry_solid", geom=g... | modulus-toolchain-master | examples/PINNs/01-PracticeProblems/solutions/s3p3.py |
from cfg import *
[x, y], [u, v, pp] = p.add_neural_network(name="NN", inputs=["x", "y"], outputs=["u", "v", "p"])
w,h = 2,1
r1 = p.Rectangle("r1", (0,0), (w,h))
ch1 = p.Channel2D("ch1", (0,0), (w,h))
inlet = p.add_boundary_subdomain("inlet", geom=r1, criteria=Eq(x,0))
outlet = p.add_boundary_subdomain("outlet", geo... | modulus-toolchain-master | examples/PINNs/01-PracticeProblems/solutions/s2p1b.py |
from cfg import *
import sympy as sp
# HEAT
[x, y], [T] = p.add_neural_network(name="NN_Tsolid", inputs=["x", "y"], outputs=[ "Tsolid"])
geo_solid = p.Rectangle("rect", (0,0), (1,1))
interior_solid = p.add_interior_subdomain("interior_solid", geom=geo_solid)
bdry_solid = p.add_boundary_subdomain("bdry_solid", geom=g... | modulus-toolchain-master | examples/PINNs/01-PracticeProblems/solutions/s3p2c.py |
from cfg import *
import sympy as sp
[x, y], [T] = p.add_neural_network(name="NN_Tsolid", inputs=["x", "y"], outputs=[ "Tsolid"])
geo_solid = p.Rectangle("rect", (0,0), (1,1))
interior_solid = p.add_interior_subdomain("interior_solid", geom=geo_solid)
bdry_solid = p.add_boundary_subdomain("bdry_solid", geom=geo_solid... | modulus-toolchain-master | examples/PINNs/01-PracticeProblems/solutions/s3p1b.py |
from cfg import *
import sympy as sp
# HEAT
[x, y], [T] = p.add_neural_network(name="NN_Tsolid", inputs=["x", "y"], outputs=[ "Tsolid"])
geo_solid = p.Rectangle("rect", (0,0), (1,1))
interior_solid = p.add_interior_subdomain("interior_solid", geom=geo_solid)
bdry_solid = p.add_boundary_subdomain("bdry_solid", geom=g... | modulus-toolchain-master | examples/PINNs/01-PracticeProblems/solutions/s3p2b.py |
from cfg import *
[x, y], sOuts = p.add_neural_network(name="NN", inputs=["x", "y"], outputs=["u", "v"])
u, v = sOuts
e_xx = p.add_submodel("epsilon_xx", u.diff(x))
e_yy = p.add_submodel("epsilon_yy", v.diff(y))
e_xy = p.add_submodel("epsilon_xy", 0.50 * u.diff(y) + 0.50 * v.diff(x))
# https://www.mathworks.com/mat... | modulus-toolchain-master | examples/PINNs/02-StructuralAnalysis/struct_2d_problem.py |
from cfg import *
[x, y, z, R], sOuts = p.add_neural_network(
name="NN", inputs=["x", "y", "z", "R"], outputs=["u", "v", "w"]
)
u, v, w = sOuts
params = {R: (10, 20)}
e_xx = p.add_submodel("epsilon_xx", u.diff(x))
e_yy = p.add_submodel("epsilon_yy", v.diff(y))
e_zz = p.add_submodel("epsilon_zz", w.diff(z))
e_xy... | modulus-toolchain-master | examples/PINNs/02-StructuralAnalysis/struct_3d_problem.py |
modulus-toolchain-master | mtc/__init__.py | |
from sympy import Symbol, Function, Or, And, Eq, Abs, Integral, expand
import sympy
import os, sys
def load_template(filename):
with open(os.path.join(os.path.dirname(__file__), filename)) as f:
return f.read()
def load_yaml(filename):
"""Loads a YAML file using a path relative to where this module... | modulus-toolchain-master | mtc/problem.py |
import click
import os, sys
# def load_template(filename):
# with open(os.path.join(os.path.dirname(__file__), filename)) as f:
# return f.read()
MTC_ROOT = os.path.dirname(__file__)
@click.group()
def cli():
pass
@cli.command()
@click.argument("project-name")
def create(project_name):
"""Creat... | modulus-toolchain-master | mtc/mtc.py |
import os
def load_yaml(filename):
"""Loads a YAML file using a path relative to where this module resides"""
import yaml
with open(os.path.join(os.path.dirname(__file__), filename)) as f:
return yaml.safe_load(f)
def load_config(path="./"):
import yaml
conf_path = os.path.join(path, "... | modulus-toolchain-master | mtc/config_utils.py |
from sympy import Symbol, Function, Or, And, Eq, Abs, Integral, expand
import sympy
import sympy as sp
from jinja2 import Template
import os, sys
import h5py
def load_template(filename):
import jinja2 as j
path = os.path.join(os.path.dirname(__file__), "templates", "fno-problem")
env = j.Environment(lo... | modulus-toolchain-master | mtc/fno_problem.py |
modulus-toolchain-master | mtc/docs/__init__.py | |
import os
from jinja2 import Template
def load_template(filename):
with open(os.path.join(os.path.dirname(__file__), filename)) as f:
return f.read()
def compile(problem):
assert (
"x" in problem._vars and "y" in problem._vars
), "Problem geometry must be 2D or 3D"
t_file = "warp_geo... | modulus-toolchain-master | mtc/compile/target_geometry.py |
modulus-toolchain-master | mtc/compile/__init__.py | |
import warp as wp
wp.init()
## SDF Helpers
# subtraction
@wp.func
def op_subtract(d1: float, d2: float):
return -wp.min(-d1, d2)
# intersection
@wp.func
def op_intersect(d1: float, d2: float):
return wp.max(d1, d2)
# union
@wp.func
def op_union(d1: float, d2: float):
return wp.min(d1, d2)
# signed sph... | modulus-toolchain-master | mtc/compile/templates/warp_geometry.py |
import warp as wp
wp.init()
## Custom Code (from problem.py)
{{custom_warp_code}}
## SDF Helpers
# subtraction
@wp.func
def op_subtract(d1: float, d2: float):
return -wp.min(-d1, d2)
# intersection
@wp.func
def op_intersect(d1: float, d2: float):
return wp.max(d1, d2)
# union
@wp.func
def op_union(d1: fl... | modulus-toolchain-master | mtc/compile/templates/warp_geometry_2d.py |
def make_infer_fn(outputs=[{% for item in _submodels %}'{{ item }}',{% endfor %}]):
coll_models=[{% for item in coll_models %}'{{ item }}',{% endfor %}]
invals = {str(v): np.array([0]).reshape(-1, 1) for v in [{% for item in _vars %}'{{ item }}',{% endfor %}]}
# requires_grad = False
requires_gra... | modulus-toolchain-master | mtc/templates/inference_section.py |
from mtc.problem import PINNProblem
from mtc.fno_problem import FNOProblem
from mtc.problem import *
PINN = PINNProblem("[PINN] %%projname%%")
FNO = FNOProblem("[PINO] %%projname%%")
PINO = FNO
p = PINN
| modulus-toolchain-master | mtc/templates/cfg.py |
from modulus.sym.solver import Solver
from modulus.sym.domain import Domain
from modulus.sym.geometry.primitives_1d import Line1D, Point1D
from modulus.sym.geometry.primitives_2d import Rectangle, Circle, Polygon, Line, Channel2D
from modulus.sym.geometry.primitives_3d import Box, Sphere, Cylinder
from modulus.sym.dom... | modulus-toolchain-master | mtc/templates/train-imports.py |
from cfg import *
# Select Problem Type
p = PINN
# p = FNO # uncomment to select a PINO/FNO problem type
# -------------------
# Suggested structure (PINN)
#
# 1. Define problem variables and unknown functions; e.g.,
# [x, y], [u] = p.add_neural_network(name="NN", inputs=["x", "y"], outputs=["u"])
#
# 2. Define g... | modulus-toolchain-master | mtc/templates/problem.py |
from typing import Dict
import modulus
from modulus.sym.hydra import instantiate_arch, ModulusConfig
from modulus.sym.key import Key
from modulus.sym.node import Node
from modulus.sym.solver import Solver
from modulus.sym.domain import Domain
from modulus.sym.domain.constraint import SupervisedGridConstraint
from mod... | modulus-toolchain-master | mtc/templates/fno-problem/train.py |
from typing import Dict
# import modulus
from modulus.sym.hydra import instantiate_arch, ModulusConfig
from modulus.sym.key import Key
from modulus.sym.node import Node
from modulus.sym.graph import Graph
from modulus.sym.solver import Solver
from modulus.sym.domain import Domain
from modulus.sym.domain.constraint im... | modulus-toolchain-master | mtc/templates/fno-problem/infer.py |
class FNOEquationConstraint(torch.nn.Module):
"Custom Equation Constraint"
def __init__(self, vars, gridvarfuncs, eq_srepr, outvar, onFunc, dirichlet_gen_conds, dirichlet_conds, neumann_conds, ctype="interior", criteria=None):
"ctype in ['interior', 'boundary']"
ctypes=['interior', 'boundary']
... | modulus-toolchain-master | mtc/templates/fno-problem/constraints.py |
modulus-toolchain-master | mtc/templates/conf/__init__.py | |
from __future__ import print_function
from setuptools import setup, find_packages, Command
from setuptools.command.sdist import sdist
from setuptools.command.build_py import build_py
from setuptools.command.egg_info import egg_info
from subprocess import check_call
import os
import sys
import platform
here = os.path.d... | ipyparaview-master | setup.py |
# Module version
version_info = (0, 1, 2, 'beta', 0)
# Module version stage suffix map
_specifier_ = {'alpha': 'a', 'beta': 'b', 'candidate': 'rc', 'final': ''}
# Module version accessible using ipyparaview.__version__
__version__ = '%s.%s.%s%s'%(version_info[0], version_info[1], version_info[2],
'' if version_info... | ipyparaview-master | ipyparaview/_version.py |
import math
import numpy as np
__all__ = ['rotateCameraTurntable', 'panCameraTurntable', 'zoomCameraTurntable']
def _normalize(v):
return v/np.linalg.norm(v)
def _cartToSphr(p):
#cartesian position into spherical
r = np.linalg.norm(p)
return np.array([r,
math.atan2(p[0], p[2]),
math.a... | ipyparaview-master | ipyparaview/camera_models.py |
###############################################################################
# Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at... | ipyparaview-master | ipyparaview/__init__.py |
###############################################################################
# Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at... | ipyparaview-master | ipyparaview/widgets.py |
#!/usr/bin/env python
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Un... | mlperf-common-main | setup.py |
# Copyright (c) 2020-2022, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | mlperf-common-main | mlperf_common/logging.py |
mlperf-common-main | mlperf_common/__init__.py | |
# Copyright (c) 2021-2022, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | mlperf-common-main | mlperf_common/scaleoutbridge.py |
# Copyright (c) 2022-2023, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | mlperf-common-main | mlperf_common/frameworks/mxnet.py |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | mlperf-common-main | mlperf_common/frameworks/base_mpi.py |
mlperf-common-main | mlperf_common/frameworks/__init__.py | |
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | mlperf-common-main | mlperf_common/frameworks/hugectr.py |
# Copyright (c) 2022-2023, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | mlperf-common-main | mlperf_common/frameworks/base.py |
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | mlperf-common-main | mlperf_common/frameworks/pyt.py |
#
# \file generator.py
#
# \brief Generates the CUTLASS Library's instances
#
import enum
import os.path
import shutil
import functools
import operator
import collections
from library import *
###################################################################################################
#
# Data structure model... | cutlass-main | tools/library/scripts/gemm_operation.py |
#
# \file generator.py
#
# \brief Generates the CUTLASS Library's instances
#
import re
###################################################################################################
import enum
# The following block implements enum.auto() for Python 3.5 variants that don't include it such
# as the default 3.5... | cutlass-main | tools/library/scripts/library.py |
#
# \file generator.py
#
# \brief Generates the CUTLASS Library's instances
#
import enum
import os.path
import shutil
from library import *
from gemm_operation import *
from rank_k_operation import *
from rank_2k_operation import *
from trmm_operation import *
from symm_operation import *
from conv2d_operation impor... | cutlass-main | tools/library/scripts/manifest.py |
#
# \file generator.py
#
# \brief Generates the CUTLASS Library's instances
#
#
import enum
import os.path
import shutil
import functools
import operator
from library import *
###################################################################################################
#
# Data structure modeling a Rank K up... | cutlass-main | tools/library/scripts/rank_k_operation.py |
#################################################################################################
#
# Copyright (c) 2017 - 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: BSD-3-Clause
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitt... | cutlass-main | tools/library/scripts/rt.py |
cutlass-main | tools/library/scripts/__init__.py | |
#
# \file generator.py
#
# \brief Generates the CUTLASS Library's instances
#
#
import enum
import os.path
import shutil
from library import *
###################################################################################################
#
class Conv2dOperation:
#
def __init__(self, conv_kind, iterator_alg... | cutlass-main | tools/library/scripts/conv2d_operation.py |
#
# \file generator.py
#
# \brief Generates the CUTLASS Library's instances
#
import enum
import os.path
import shutil
import argparse
import logging
from library import *
from manifest import *
from itertools import product
############################################################################################... | cutlass-main | tools/library/scripts/generator.py |
#
# \file generator.py
#
# \brief Generates the CUTLASS Library's instances
#
#
import enum
import os.path
import shutil
from library import *
###################################################################################################
#
class Conv3dOperation:
#
def __init__(self, conv_kind, iterator_alg... | cutlass-main | tools/library/scripts/conv3d_operation.py |
#
# \file generator.py
#
# \brief Generates the CUTLASS Library's instances
#
#
import enum
import os.path
import shutil
import functools
import operator
from library import *
###################################################################################################
#
# Data structure modeling a Rank K up... | cutlass-main | tools/library/scripts/rank_2k_operation.py |
#
# \file generator.py
#
# \brief Generates the CUTLASS Library's instances
#
#
import enum
import os.path
import shutil
import functools
import operator
from library import *
###################################################################################################
#
# Data structure modeling a Symm upda... | cutlass-main | tools/library/scripts/symm_operation.py |
#
# \file generator.py
#
# \brief Generates the CUTLASS Library's instances
#
#
import enum
import os.path
import shutil
import functools
import operator
from library import *
###################################################################################################
#
# Data structure modeling a TRMM oper... | cutlass-main | tools/library/scripts/trmm_operation.py |
# Copyright (c) 2017 - 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: BSD-3-Clause
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain... | cutlass-main | test/unit/gemm/device/simt_sm50.py |
#################################################################################################
#
# Copyright (c) 2023 - 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: BSD-3-Clause
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitt... | cutlass-main | test/python/interface/gemm_interface.py |
#################################################################################################
#
# Copyright (c) 2023 - 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: BSD-3-Clause
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitt... | cutlass-main | test/python/interface/conv2d_interface.py |
#################################################################################################
#
# Copyright (c) 2023 - 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: BSD-3-Clause
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitt... | cutlass-main | test/python/interface/utils.py |
#################################################################################################
#
# Copyright (c) 2023 - 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: BSD-3-Clause
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitt... | cutlass-main | test/python/conv2d/conv2d_sm80.py |
#################################################################################################
#
# Copyright (c) 2023 - 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: BSD-3-Clause
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitt... | cutlass-main | test/python/conv2d/conv2d_test_utils.py |
#################################################################################################
#
# Copyright (c) 2023 - 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: BSD-3-Clause
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitt... | cutlass-main | test/python/conv2d/run_all_tests.py |
#################################################################################################
#
# Copyright (c) 2017 - 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: BSD-3-Clause
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitt... | cutlass-main | test/python/backend/conv/conv2d_dgrad_implicit_gemm_tf32nhwc_tf32nhwc_f32nhwc_tensor_op_f32_sm80.py |
#################################################################################################
#
# Copyright (c) 2017 - 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: BSD-3-Clause
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitt... | cutlass-main | test/python/backend/conv/conv2d_dgrad_implicit_gemm_f16nhwc_f16nhwc_f32nhwc_tensor_op_f32_sm80.py |
#################################################################################################
#
# Copyright (c) 2017 - 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: BSD-3-Clause
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitt... | cutlass-main | test/python/backend/conv/conv2d_dgrad_implicit_gemm_f16nhwc_f16nhwc_f16nhwc_tensor_op_f16_sm80.py |
#################################################################################################
#
# Copyright (c) 2017 - 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: BSD-3-Clause
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitt... | cutlass-main | test/python/backend/conv/conv2d_strided_dgrad_implicit_gemm_f16nhwc_f16nhwc_f32nhwc_tensor_op_f32_sm80.py |
#################################################################################################
#
# Copyright (c) 2017 - 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: BSD-3-Clause
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitt... | cutlass-main | test/python/backend/conv/conv2d_fprop_few_channels_f16nhwc_f16nhwc_f16nhwc_tensor_op_f32_sm80.py |
#################################################################################################
#
# Copyright (c) 2017 - 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: BSD-3-Clause
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitt... | cutlass-main | test/python/backend/conv/conv2d_wgrad_implicit_gemm_f16nhwc_f16nhwc_f32nhwc_tensor_op_f32_sm80.py |
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