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2 changes: 1 addition & 1 deletion .github/workflows/python-package.yml
Original file line number Diff line number Diff line change
@@ -6,7 +6,7 @@ on:
pull_request:
branches: [ master ]
env:
DASK_SERVER_IP: 52.190.25.183
DASK_SERVER_IP: ${{ secrets.DASK_SERVER_IP }}
BLOB_ACCOUNT_NAME: ${{ secrets.BLOB_ACCOUNT_NAME }}
BLOB_ACCOUNT_KEY: ${{ secrets.BLOB_ACCOUNT_KEY }}
jobs:
2 changes: 1 addition & 1 deletion fwi/run.py
Original file line number Diff line number Diff line change
@@ -251,7 +251,7 @@ def fwi_gradient(vp_in, nshots, client, solver, shots_container, auth, scale_gra
solver.model.update("vp", vp)

# Dask enforces this for large objects
f_solver = client.scatter(solver, broadcast=True)
f_solver = client.scatter(solver, broadcast=False)

futures = []

4 changes: 2 additions & 2 deletions fwi/shotprocessors.py
Original file line number Diff line number Diff line change
@@ -27,10 +27,10 @@ def process_shot(i, solver, shots_container, auth, exclude_boundaries=True, dt=N
rec0, u0, _ = solver.forward(save=True, dt=dt)

residual = Receiver(name='rec', grid=solver.model.grid, data=rec0.data - rec,
time_range=solver.geometry.time_axis,
time_range=solver.geometry.time_axis, dtype=solver.model.dtype,
coordinates=solver.geometry.rec_positions)

objective = .5*np.linalg.norm(residual.data.ravel())**2
objective = (.5*np.linalg.norm(residual.data.ravel())**2).astype(solver.model.dtype)

grad, _ = solver.gradient(residual, u=u0, dt=dt)

6 changes: 3 additions & 3 deletions kubernetes/dask-cluster.yaml
Original file line number Diff line number Diff line change
@@ -22,7 +22,7 @@ spec:
"beta.kubernetes.io/os": linux
containers:
- name: devito-server
image: devitoaks.azurecr.io/daks-base:v8
image: devitoaks.azurecr.io/daks-base:v9
command: ['/venv/bin/dask-scheduler']
ports:
- containerPort: 8786
@@ -52,7 +52,7 @@ kind: Deployment
metadata:
name: devito-worker
spec:
replicas: 15
replicas: 2
strategy:
rollingUpdate:
maxSurge: 1
@@ -83,7 +83,7 @@ spec:
value: "cores"
- name: "OMP_NUM_THREADS"
value: "4"
image: devitoaks.azurecr.io/daks-base:v8
image: devitoaks.azurecr.io/daks-base:v9
command: ['/venv/bin/dask-worker', 'tcp://devito-server:8786', '--memory-limit', '13G', '--resources', 'tasks=1', '--nprocs', '1', '--nthreads', '1']
ports:
- containerPort: 80
2 changes: 1 addition & 1 deletion requirements.txt
Original file line number Diff line number Diff line change
@@ -3,7 +3,7 @@ tqdm
bokeh
azure-storage-blob==2.1.0
devito
dask
dask==2.22.0
distributed
numpy
cloudpickle
4 changes: 2 additions & 2 deletions tests/conftest.py
Original file line number Diff line number Diff line change
@@ -15,7 +15,7 @@ def auth():
def model():
initial_model_filename = "overthrust_3D_initial_model_2D.h5"
datakey = "m0"
return "%s:%s" % (initial_model_filename, datakey)
return initial_model_filename, datakey


@pytest.fixture
@@ -40,7 +40,7 @@ def nbl():

@pytest.fixture
def solver_params(model, auth, tn, so, dtype, nbl):
initial_model_filename, datakey = model.split(":")
initial_model_filename, datakey = model
return {'h5_file': Blob("models", initial_model_filename, auth=auth), 'tn': tn,
'space_order': so, 'dtype': dtype, 'datakey': datakey, 'nbl': nbl,
'opt': ('noop', {'openmp': True, 'par-dynamic-work': 1000})}
78 changes: 74 additions & 4 deletions tests/test_dask.py
Original file line number Diff line number Diff line change
@@ -20,12 +20,57 @@ def remote_test():
assert(result)


def test_dask_pickling(solver, client):
@pytest.mark.skip(reason="Platforms don't always match")
def test_dask_configuration(solver, client):

def get_configuration():
from devito import configuration
return str(configuration)

config_future = client.submit(get_configuration)

wait(config_future)

config_remote = config_future.result()
print("Remote")
print(config_remote)
print("Local")
print(get_configuration())
assert(config_remote == get_configuration())


@pytest.mark.skip(reason="Sonames are different if platforms are different")
def test_dask_soname(solver, client):
op = solver.op_fwd()

def soname(op):
return op._soname

# Force local JITing
rec1, u1, _ = solver.forward()

soname_future = client.submit(soname, op)

wait(soname_future)

soname_remote = soname_future.result()

assert(soname_remote == op._soname)


def test_dask_pickling(solver, client):

def noop_function(x):
return x
# Important that the solver is sent before being JITed
# See above skipped test for reason
solver_future = client.submit(noop_function, solver)

wait(solver_future)

solver2 = solver_future.result()

rec1, u1, _ = solver.forward()
rec_future = client.submit(noop_function, rec1)
u_future = client.submit(noop_function, u1)

@@ -41,14 +86,39 @@ def noop_function(x):

assert(np.allclose(u1.data, u2.data, atol=0., rtol=0.))

assert(solver2.model.shape == solver.model.shape)
assert(solver2.model.nbl == solver.model.nbl)
assert(solver2.model.origin == solver.model.origin)
assert(solver2.model.spacing == solver.model.spacing)
assert(solver2.model.dtype == solver.model.dtype)
assert((solver2.geometry.src_positions == solver.geometry.src_positions).all())
assert((solver2.geometry.rec_positions == solver.geometry.rec_positions).all())
assert(solver2.geometry.f0 == solver.geometry.f0)
assert(solver2.geometry.tn == solver.geometry.tn)
assert(solver2.geometry.t0 == solver.geometry.t0)
assert(solver2.geometry.dt == solver.geometry.dt)
assert(solver2.geometry.nt == solver.geometry.nt)
assert(solver2.space_order == solver.space_order)
assert(solver2.kernel == solver.kernel)
assert(solver2._kwargs == solver._kwargs)

assert(str(solver2.op_fwd()) == str(solver.op_fwd()))
assert(str(solver2.op_grad()) == str(solver.op_grad()))


@pytest.mark.skip(reason="Numerical mismatch")
def test_remote_devito(solver, client):
future = client.submit(solver.forward)
rec1, u1, _ = solver.forward()
wait(future)
rec2, u2, _ = future.result()
print(np.linalg.norm(rec1.data))
print(np.linalg.norm(rec2.data))
assert(np.allclose(rec1.data, rec2.data, atol=0., rtol=0.))
assert((u1.data == u2.data).all())
print(np.linalg.norm(u1.data), np.linalg.norm(u2.data))
error_rec = rec1.data - rec2.data
rel_rec = error_rec/rec1.data
print("rec", np.min(error_rec), np.max(error_rec), np.min(rel_rec), np.max(rel_rec))
error_u = np.absolute(u1.data - u2.data)
rel_u = error_u/u1.data
print("u", np.min(error_u), np.max(error_u), np.min(rel_u), np.max(rel_u))
assert(np.allclose(rec1.data, rec2.data, atol=1e-7, rtol=1e-5))
assert(np.allclose(u1.data, u2.data, atol=1e-7, rtol=1e-5))
86 changes: 22 additions & 64 deletions tests/test_fwi.py
Original file line number Diff line number Diff line change
@@ -6,7 +6,6 @@
from fwi.run import initial_setup, fwi_gradient
from fwi.dasksetup import setup_dask
from fwi.io import Blob
from fwi.overthrust import overthrust_solver_iso
from fwi.shotprocessors import process_shot, process_shot_checkpointed
from util import mat2vec, trim_boundary, vec2mat

@@ -16,7 +15,7 @@ def shots_container():
return "shots-iso-40-nbl-40-so-16"


def fwi_gradient_local(vp_in, nshots, solver, shots_container):
def fwi_gradient_local(vp_in, nshots, solver, shots_container, auth):
model = solver.model

vp_in = np.array(vec2mat(vp_in, solver.model.vp.shape), dtype=solver.model.dtype)
@@ -30,32 +29,26 @@ def fwi_gradient_local(vp_in, nshots, solver, shots_container):
grad = np.zeros(model.vp.shape)

for i in range(nshots):
o, g = process_shot(i, solver, shots_container, exclude_boundaries=False)
o, g = process_shot(i, solver, shots_container, auth, exclude_boundaries=False)
objective += o
grad += g

return objective, -mat2vec(grad).astype(np.float64)


@pytest.mark.skip(reason="Hangs indefinitely")
def test_equivalence_local_remote_single_shot(shots_container):
@pytest.mark.xfail(reason="Numerical mismatch")
def test_equivalence_local_remote_single_shot(shots_container, solver, auth, client):
initial_model_filename, tn, dtype, so, nbl = "overthrust_3D_initial_model_2D.h5", 4000, np.float32, 6, 40
model, _, bounds = initial_setup(filename=Blob("models", initial_model_filename), tn=tn, dtype=dtype,
model, _, bounds = initial_setup(filename=Blob("models", initial_model_filename, auth=auth), tn=tn, dtype=dtype,
space_order=so, nbl=nbl)

solver_params = {'h5_file': Blob("models", initial_model_filename), 'tn': tn, 'space_order': so, 'dtype': dtype,
'datakey': 'm0', 'nbl': nbl}

solver = overthrust_solver_iso(**solver_params)

v0 = mat2vec(model.vp.data).astype(np.float64)

local_results = fwi_gradient_local(v0, 1, solver, shots_container)
remote_results = fwi_gradient(v0, 1, client, solver, shots_container, auth, exclude_boundaries=False,
scale_gradient=None, mute_water=False)

client = setup_dask()

remote_results = fwi_gradient(v0, 1, client, solver, shots_container, exclude_boundaries=False,
scale_gradient=False, mute_water=False)
# Calling local version first leads to random "CommClosed" errors
local_results = fwi_gradient_local(v0, 1, solver, shots_container, auth)

np.testing.assert_approx_equal(local_results[0], remote_results[0])

@@ -77,31 +70,18 @@ def test_vec2mat():
@pytest.mark.xfail(reason="Numerical mismatch")
@pytest.mark.parametrize('shot_id', [20])
@pytest.mark.parametrize('exclude_boundaries', [True, False])
def test_shot(shot_id, shots_container, exclude_boundaries):
initial_model_filename = "overthrust_3D_initial_model_2D.h5"
tn = 4000
dtype = np.float32
so = 6
nbl = 40
exclude_boundaries = True
shot_id = 1
solver_params = {'h5_file': Blob("models", initial_model_filename), 'tn': tn,
'space_order': so, 'dtype': dtype, 'datakey': 'm0', 'nbl': nbl,
'opt': ('noop', {'openmp': True, 'par-dynamic-work': 1000})}

solver1 = overthrust_solver_iso(**solver_params)
o1, grad1 = process_shot(shot_id, solver1, shots_container, exclude_boundaries)
def test_shot(shot_id, shots_container, exclude_boundaries, solver, auth):
client = setup_dask()
future = client.submit(process_shot, shot_id, solver1, shots_container, exclude_boundaries)
future = client.submit(process_shot, shot_id, solver, shots_container, auth, exclude_boundaries)
wait(future)

o2, grad2 = future.result()
o1, grad1 = process_shot(shot_id, solver, shots_container, auth, exclude_boundaries)

assert(np.allclose(grad1, grad2, atol=0., rtol=0.))
assert(o1 == o2)


def test_equivalence_shot_checkpointing(shots_container, auth):
def test_equivalence_shot_checkpointing(shots_container, auth, solver):
initial_model_filename = "overthrust_3D_initial_model_2D.h5"
tn = 4000
dtype = np.float32
@@ -111,41 +91,27 @@ def test_equivalence_shot_checkpointing(shots_container, auth):
water_depth = 20
shot_id = 1

solver_params = {'h5_file': Blob("models", initial_model_filename, auth=auth), 'tn': tn,
'space_order': so, 'dtype': dtype, 'datakey': 'm0', 'nbl': nbl,
'opt': ('noop', {'openmp': True, 'par-dynamic-work': 1000})}

solver1 = overthrust_solver_iso(**solver_params)
solver2 = overthrust_solver_iso(**solver_params)

model, geometry, _ = initial_setup(Blob("models", initial_model_filename, auth=auth), tn, dtype, so, nbl,
datakey="m0", exclude_boundaries=exclude_boundaries,
water_depth=water_depth)
o2, grad2 = process_shot(shot_id, solver1, shots_container, auth, exclude_boundaries)
o1, grad1 = process_shot_checkpointed(shot_id, solver2, shots_container, auth, exclude_boundaries)
o2, grad2 = process_shot(shot_id, solver, shots_container, auth, exclude_boundaries)
o1, grad1 = process_shot_checkpointed(shot_id, solver, shots_container, auth, exclude_boundaries)

np.testing.assert_approx_equal(o1, o2, significant=5)
assert(np.allclose(grad1, grad2, rtol=1e-4))
np.testing.assert_approx_equal(o1, o2, significant=7)
assert(np.allclose(grad1, grad2, atol=0.))


@pytest.mark.skip(reason="Hangs indefinitely")
@pytest.mark.parametrize('mute_water', [True, False])
@pytest.mark.parametrize('scale_gradient', [None, 'L', 'W'])
@pytest.mark.parametrize('exclude_boundaries', [True, False])
def test_equivalence_checkpointing(shots_container, exclude_boundaries, scale_gradient, mute_water):
def test_equivalence_checkpointing(shots_container, exclude_boundaries, scale_gradient, mute_water, client, solver, auth):
initial_model_filename = "overthrust_3D_initial_model_2D.h5"
tn = 4000
dtype = np.float32
so = 6
nbl = 40
water_depth = 20
nshots = 1
client = setup_dask()

solver_params = {'h5_file': Blob("models", initial_model_filename), 'tn': tn,
'space_order': so, 'dtype': dtype, 'datakey': 'm0', 'nbl': nbl}

solver = overthrust_solver_iso(**solver_params)

model, geometry, _ = initial_setup(initial_model_filename, tn, dtype, so, nbl,
datakey="m0", exclude_boundaries=exclude_boundaries,
@@ -156,23 +122,15 @@ def test_equivalence_checkpointing(shots_container, exclude_boundaries, scale_gr
else:
v0 = mat2vec(model.vp.data).astype(np.float64)

o1, grad1 = fwi_gradient(v0, nshots, client, solver, shots_container, scale_gradient, mute_water,
o1, grad1 = fwi_gradient(v0, nshots, client, solver, shots_container, auth, scale_gradient, mute_water,
exclude_boundaries, water_depth, checkpointing=True)

o2, grad2 = fwi_gradient(v0, nshots, client, solver, shots_container, scale_gradient, mute_water,
o2, grad2 = fwi_gradient(v0, nshots, client, solver, shots_container, auth, scale_gradient, mute_water,
exclude_boundaries, water_depth)
print(o1, np.linalg.norm(grad1), grad1.shape)
print(o2, np.linalg.norm(grad2), grad2.shape)

grad1_diag = [grad1[k, k] for k in range(40)]
grad2_diag = [grad2[k, k] for k in range(40)]

print(grad1_diag)
print(grad2_diag)

np.testing.assert_approx_equal(o1, o2, significant=5)
np.testing.assert_approx_equal(o1, o2, significant=7)

np.testing.assert_array_almost_equal(grad1, grad2, significant=5)
np.testing.assert_array_almost_equal(grad1, grad2)


if __name__ == "__main__":