/-- The derivative of the convolution `f * g` is given by `f * Dg`, when `f` is locally integrable
and `g` is `C^1` and compactly supported. Version where `g` depends on an additional parameter in an
open subset `s` of a parameter space `P` (and the compact support `k` is independent of the
parameter in `s`). -/
theorem hasFDerivAt_convolution_right_with_param {g : P → G → E'} {s : Set P} {k : Set G}
    (hs : IsOpen s) (hk : IsCompact k) (hgs : ∀ p, ∀ x, p ∈ s → x ∉ k → g p x = 0)
    (hf : LocallyIntegrable f μ) (hg : ContDiffOn 𝕜 1 (↿g) (s ×ˢ univ)) (q₀ : P × G)
    (hq₀ : q₀.1 ∈ s) :
    HasFDerivAt (fun q : P × G => (f ⋆[L, μ] g q.1) q.2)
      ((f ⋆[L.precompR (P × G), μ] fun x : G => fderiv 𝕜 (↿g) (q₀.1, x)) q₀.2) q₀ := by
  let g' := fderiv 𝕜 ↿g
  have A : ∀ p ∈ s, Continuous (g p) := fun p hp ↦ by
    refine hg.continuousOn.comp_continuous (continuous_const.prod_mk continuous_id') fun x => ?_
    simpa only [prod_mk_mem_set_prod_eq, mem_univ, and_true_iff] using hp
  have A' : ∀ q : P × G, q.1 ∈ s → s ×ˢ univ ∈ 𝓝 q := fun q hq ↦ by
    apply (hs.prod isOpen_univ).mem_nhds
    simpa only [mem_prod, mem_univ, and_true_iff] using hq
  -- The derivative of `g` vanishes away from `k`.
  have g'_zero : ∀ p x, p ∈ s → x ∉ k → g' (p, x) = 0 := by
    intro p x hp hx
    refine' (hasFDerivAt_zero_of_eventually_const 0 _).fderiv
    have M2 : kᶜ ∈ 𝓝 x := hk.isClosed.isOpen_compl.mem_nhds hx
    have M1 : s ∈ 𝓝 p := hs.mem_nhds hp
    rw [nhds_prod_eq]
    filter_upwards [prod_mem_prod M1 M2]
    rintro ⟨p, y⟩ ⟨hp, hy⟩
    exact hgs p y hp hy
  /- We find a small neighborhood of `{q₀.1} × k` on which the derivative is uniformly bounded. This
    follows from the continuity at all points of the compact set `k`. -/
  obtain ⟨ε, C, εpos, h₀ε, hε⟩ :
      ∃ ε C, 0 < ε ∧ ball q₀.1 ε ⊆ s ∧ ∀ p x, ‖p - q₀.1‖ < ε → ‖g' (p, x)‖ ≤ C := by
    have A : IsCompact ({q₀.1} ×ˢ k) := isCompact_singleton.prod hk
    obtain ⟨t, kt, t_open, ht⟩ : ∃ t, {q₀.1} ×ˢ k ⊆ t ∧ IsOpen t ∧ IsBounded (g' '' t) := by
      have B : ContinuousOn g' (s ×ˢ univ) :=
        hg.continuousOn_fderiv_of_isOpen (hs.prod isOpen_univ) le_rfl
      apply exists_isOpen_isBounded_image_of_isCompact_of_continuousOn A (hs.prod isOpen_univ) _ B
      simp only [prod_subset_prod_iff, hq₀, singleton_subset_iff, subset_univ, and_self_iff,
        true_or_iff]
    obtain ⟨ε, εpos, hε, h'ε⟩ :
      ∃ ε : ℝ, 0 < ε ∧ thickening ε ({q₀.fst} ×ˢ k) ⊆ t ∧ ball q₀.1 ε ⊆ s := by
      obtain ⟨ε, εpos, hε⟩ : ∃ ε : ℝ, 0 < ε ∧ thickening ε (({q₀.fst} : Set P) ×ˢ k) ⊆ t
      · exact A.exists_thickening_subset_open t_open kt
      obtain ⟨δ, δpos, hδ⟩ : ∃ δ : ℝ, 0 < δ ∧ ball q₀.1 δ ⊆ s
      · exact Metric.isOpen_iff.1 hs _ hq₀
      refine' ⟨min ε δ, lt_min εpos δpos, _, _⟩
      · exact Subset.trans (thickening_mono (min_le_left _ _) _) hε
      · exact Subset.trans (ball_subset_ball (min_le_right _ _)) hδ
    obtain ⟨C, Cpos, hC⟩ : ∃ C, 0 < C ∧ g' '' t ⊆ closedBall 0 C; exact ht.subset_closedBall_lt 0 0
    refine' ⟨ε, C, εpos, h'ε, fun p x hp => _⟩
    have hps : p ∈ s := h'ε (mem_ball_iff_norm.2 hp)
    by_cases hx : x ∈ k
    · have H : (p, x) ∈ t := by
        apply hε
        refine' mem_thickening_iff.2 ⟨(q₀.1, x), _, _⟩
        · simp only [hx, singleton_prod, mem_image, Prod.mk.inj_iff, eq_self_iff_true, true_and_iff,
            exists_eq_right]
        · rw [← dist_eq_norm] at hp
          simpa only [Prod.dist_eq, εpos, dist_self, max_lt_iff, and_true_iff] using hp
      have : g' (p, x) ∈ closedBall (0 : P × G →L[𝕜] E') C := hC (mem_image_of_mem _ H)
      rwa [mem_closedBall_zero_iff] at this
    · have : g' (p, x) = 0 := g'_zero _ _ hps hx
      rw [this]
      simpa only [norm_zero] using Cpos.le
  /- Now, we wish to apply a theorem on differentiation of integrals. For this, we need to check
    trivial measurability or integrability assumptions (in `I1`, `I2`, `I3`), as well as a uniform
    integrability assumption over the derivative (in `I4` and `I5`) and pointwise differentiability
    in `I6`. -/
  have I1 :
    ∀ᶠ x : P × G in 𝓝 q₀, AEStronglyMeasurable (fun a : G => L (f a) (g x.1 (x.2 - a))) μ := by
    filter_upwards [A' q₀ hq₀]
    rintro ⟨p, x⟩ ⟨hp, -⟩
    refine' (HasCompactSupport.convolutionExists_right L _ hf (A _ hp) _).1
    apply hk.of_isClosed_subset (isClosed_tsupport _)
    exact closure_minimal (support_subset_iff'.2 fun z hz => hgs _ _ hp hz) hk.isClosed
  have I2 : Integrable (fun a : G => L (f a) (g q₀.1 (q₀.2 - a))) μ := by
    have M : HasCompactSupport (g q₀.1) := HasCompactSupport.intro hk fun x hx => hgs q₀.1 x hq₀ hx
    apply M.convolutionExists_right L hf (A q₀.1 hq₀) q₀.2
  have I3 : AEStronglyMeasurable (fun a : G => (L (f a)).comp (g' (q₀.fst, q₀.snd - a))) μ := by
    have T : HasCompactSupport fun y => g' (q₀.1, y) :=
      HasCompactSupport.intro hk fun x hx => g'_zero q₀.1 x hq₀ hx
    apply (HasCompactSupport.convolutionExists_right (L.precompR (P × G) : _) T hf _ q₀.2).1
    have : ContinuousOn g' (s ×ˢ univ) :=
      hg.continuousOn_fderiv_of_isOpen (hs.prod isOpen_univ) le_rfl
    apply this.comp_continuous (continuous_const.prod_mk continuous_id')
    intro x
    simpa only [prod_mk_mem_set_prod_eq, mem_univ, and_true_iff] using hq₀
  set K' := (-k + {q₀.2} : Set G) with K'_def
  have hK' : IsCompact K' := hk.neg.add isCompact_singleton
  obtain ⟨U, U_open, K'U, hU⟩ : ∃ U, IsOpen U ∧ K' ⊆ U ∧ IntegrableOn f U μ
  exact hf.integrableOn_nhds_isCompact hK'
  obtain ⟨δ, δpos, δε, hδ⟩ : ∃ δ, (0 : ℝ) < δ ∧ δ ≤ ε ∧ K' + ball 0 δ ⊆ U := by
    obtain ⟨V, V_mem, hV⟩ : ∃ V ∈ 𝓝 (0 : G), K' + V ⊆ U :=
      compact_open_separated_add_right hK' U_open K'U
    rcases Metric.mem_nhds_iff.1 V_mem with ⟨δ, δpos, hδ⟩
    refine' ⟨min δ ε, lt_min δpos εpos, min_le_right δ ε, _⟩
    exact (add_subset_add_left ((ball_subset_ball (min_le_left _ _)).trans hδ)).trans hV
  -- Porting note: added to speed up the line below.
  letI := ContinuousLinearMap.hasOpNorm (𝕜 := 𝕜) (𝕜₂ := 𝕜) (E := E)
    (F := (P × G →L[𝕜] E') →L[𝕜] P × G →L[𝕜] F) (σ₁₂ := RingHom.id 𝕜)
  let bound : G → ℝ := indicator U fun t => ‖(L.precompR (P × G))‖ * ‖f t‖ * C
  have I4 : ∀ᵐ a : G ∂μ, ∀ x : P × G, dist x q₀ < δ →
      ‖L.precompR (P × G) (f a) (g' (x.fst, x.snd - a))‖ ≤ bound a := by
    apply eventually_of_forall
    intro a x hx
    rw [Prod.dist_eq, dist_eq_norm, dist_eq_norm] at hx
    have : (-tsupport fun a => g' (x.1, a)) + ball q₀.2 δ ⊆ U := by
      apply Subset.trans _ hδ
      rw [K'_def, add_assoc]
      apply add_subset_add
      · rw [neg_subset_neg]
        refine closure_minimal (support_subset_iff'.2 fun z hz => ?_) hk.isClosed
        apply g'_zero x.1 z (h₀ε _) hz
        rw [mem_ball_iff_norm]
        exact ((le_max_left _ _).trans_lt hx).trans_le δε
      · simp only [add_ball, thickening_singleton, zero_vadd, subset_rfl]
    

Proof state:
case hp
𝕜 : Type u𝕜
G : Type uG
E : Type uE
E' : Type uE'
E'' : Type uE''
F : Type uF
F' : Type uF'
F'' : Type uF''
P : Type uP
inst✝¹⁶ : NormedAddCommGroup E
inst✝¹⁵ : NormedAddCommGroup E'
inst✝¹⁴ : NormedAddCommGroup E''
inst✝¹³ : NormedAddCommGroup F
f f' : G → E
g✝ g'✝ : G → E'
x✝ x' : G
y y' : E
inst✝¹² : IsROrC 𝕜
inst✝¹¹ : NormedSpace 𝕜 E
inst✝¹⁰ : NormedSpace 𝕜 E'
inst✝⁹ : NormedSpace 𝕜 E''
inst✝⁸ : NormedSpace ℝ F
inst✝⁷ : NormedSpace 𝕜 F
inst✝⁶ : CompleteSpace F
inst✝⁵ : MeasurableSpace G
inst✝⁴ : NormedAddCommGroup G
inst✝³ : BorelSpace G
inst✝² : NormedSpace 𝕜 G
inst✝¹ : NormedAddCommGroup P
inst✝ : NormedSpace 𝕜 P
μ : Measure G
L : E →L[𝕜] E' →L[𝕜] F
g : P → G → E'
s : Set P
k : Set G
hs : IsOpen s
hk : IsCompact k
hgs : ∀ (p : P) (x : G), p ∈ s → x ∉ k → g p x = 0
hf : LocallyIntegrable f
hg : ContDiffOn 𝕜 1 (↿g) (s ×ˢ univ)
q₀ : P × G
hq₀ : q₀.1 ∈ s
g' : P × G → P × G →L[𝕜] E' := fderiv 𝕜 ↿g
A : ∀ p ∈ s, Continuous (g p)
A' : ∀ (q : P × G), q.1 ∈ s → s ×ˢ univ ∈ 𝓝 q
g'_zero : ∀ (p : P) (x : G), p ∈ s → x ∉ k → g' (p, x) = 0
ε C : ℝ
εpos : 0 < ε
h₀ε : ball q₀.1 ε ⊆ s
hε : ∀ (p : P) (x : G), ‖p - q₀.1‖ < ε → ‖g' (p, x)‖ ≤ C
I1 : ∀ᶠ (x : P × G) in 𝓝 q₀, AEStronglyMeasurable (fun a => (L (f a)) (g x.1 (x.2 - a))) μ
I2 : Integrable fun a => (L (f a)) (g q₀.1 (q₀.2 - a))
I3 : AEStronglyMeasurable (fun a => ContinuousLinearMap.comp (L (f a)) (g' (q₀.1, q₀.2 - a))) μ
K' : Set G := -k + {q₀.2}
K'_def : K' = -k + {q₀.2}
hK' : IsCompact K'
U : Set G
U_open : IsOpen U
K'U : K' ⊆ U
hU : IntegrableOn f U
δ : ℝ
δpos : 0 < δ
δε : δ ≤ ε
hδ : K' + ball 0 δ ⊆ U
this✝ : Norm (E →L[𝕜] (P × G →L[𝕜] E') →L[𝕜] P × G →L[𝕜] F) := hasOpNorm
bound : G → ℝ := indicator U fun t => ‖precompR (P × G) L‖ * ‖f t‖ * C
a : G
x : P × G
hx : max ‖x.1 - q₀.1‖ ‖x.2 - q₀.2‖ < δ
this : (-tsupport fun a => g' (x.1, a)) + ball q₀.2 δ ⊆ U
⊢ ‖((precompR (P × G) L) (f a)) (g' (x.1, x.2 - a))‖ ≤ bound a

Next tactic:
apply convolution_integrand_bound_right_of_le_of_subset _ _ _ this